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Agilent CytoGenomics 3.0

1. E1A_r60_n11 4 67 6 13 E1A_r60_n9 4 69 9 38 E1A_r60_1 4 81 5 69 Figure 26 1 color QC Report Agilent Spikelns Signal Statistics Feature Extraction for CytoGenomics Reference Guide Spike in Linearity Check for 2 color Gene Expression Using the data calculated for the above table the observed average log ratio is plotted vs the expected log ratio for each of the spike in probes A linear regression analysis is done using these values and the metrics are shown below the plot A slope of 1 y intercept of 0 and R of 1 is the ideal of such a linear regression A slope lt 1 may indicate compression such as having under corrected for background The regression coefficient R reflects reproducibility The standard deviation for each data point is shown on the plot by an error bar extending above and below the point Agilent SpikeIns Expected LogRatio Vs Observed LogRatio p E fe o _l T T k T a Fz Oo 0 50 0 00 Expected LogRatio Standard Deviation of Log Ratio Intercept 0 085 Slope 0 954 R 2 0 986 Figure 27 QC Report Agilent Spikelns Expected Log Ratio Vs Observed LogRatio Feature Extraction for CytoGenomics Reference Guide 51 Spike in Linearity Check for 1 color Gene Expression This plot is usually sigmoidal with two asymptotes one at the scanner saturation point and one at the level of signal for sequences with no specifically bound target Some microarr
2. integer integer 1 True 0 False Feature Extraction for CytoGenomics Reference Guide List of parameters and options contained within the FULL text output file FEPARAMS table Description Enables rejection of probes close to zero signal from the set of features used in the fit The option to use a polynomial surface fit method for the multiplicative detrending fit rather than LOESS This factor multiplies the negative control spread to determine the threshold signal below which low intensity features are filtered out of the multiplicative detrending fit set Shows the degree of the polynomial fit used for the multiplicative detrending The most common choices are 2 quadratic or 2nd order surface and 4 4th order surface Tests whether the replicate CVs improve i e decrease after multiplicative detrending If this choice is 1 True and the replicate CVs don t improve Feature Extraction doesn t use the multiplicative detrending for that array Specifies to use only replicated probes with multiple features normalized to their replicate average for the multiplicative detrending set Table 3 List of parameters and options contained within the FULL text output file FEPARAMS table Protocol Step Parameters Type Options Compute Bkgd BGSubtractor_ BGSubMethod integer Bias and Error 1 2 3 5 6 7 Compute Bkgd BGSubtractor_MaxPVal float Bias and Error Compute Bkgd BGSubtractor_WellAboveMulti
3. NA e Ifthe protocol has SpikeIn Used set to False then the QC metric table in the QC Report will show for values and black font instead of red green or blue fonts indicating no evaluation has been done by Feature Extraction Specialized SpikelIn plots amp tables will be omitted from the report How the curve and statistics are calculated Curve fit equation All of the statistics in the table above are calculated using a parameterized sigmoidal curve fit to the data max min ia Pa x0 w F x min where min is the level of signal for sequences with no specifically bound target and max is the upper limit of detection where x0 is the center of the data and close to the center of the linear range where w is the width of the curve on either side of x0 Curve fit calculations Before the calculations the following assumptions are made Saturation Point is fixed or close to scanner detection limit This value is Log Scanner Saturation Value 4 82 The linear range of the curve x0 w x0 w does not define the dynamic range of the data as the data is close to linear for higher multiples of w away from x0 Feature Extraction for CytoGenomics Reference Guide The asymptotes for the max and the min are not necessarily symmetric The upper asymptote is a function of scanner offset and the lower asymptote is a function of chemistry scanner noise The calculations then follow this order
4. The Feature Extraction process for l color gene expression microarrays includes only seven protocol steps and for miRNA analysis the process includes those seven steps plus a MicroRNA Analysis step The examples used below are primarily for 2 color microarrays Any differences in algorithms and functions for other microarray experiments are also explained Algorithms and functions they perform Place Grid This algorithm finds the grid to define the nominal positions of the spots on the microarray For more information on the eXtended Dynamic Range XDR extraction For an XDR algorithms for XDR extraction see extraction the grid placement is done using the high XDR Extraction Process on intensity scan i e higher PMT voltage The grid found page 170 using the high intensity scan is used as the starting point for the remaining extraction of both the high and low intensity images 160 Feature Extraction for CytoGenomics Reference Guide With version 10 x and higher of the software you no longer have to perform XDR dual scans or extractions to capture the full dynamic range of the data You can get the same dynamic range by working with the 20 bit TIFF Dynamic Range option This option is meant to be a replacement for the XDR option You capture the full dynamic range with better accuracy Choosing the XDR option may still be useful if you want to compare XDR data from the G2565BA Scanner with XDR data from the G2565CA Scan
5. a The Min is estimated by taking all the SpikeIn data and for each sequence calculating the BackgroundSubtracted SignalAverage the Median of the Log of the processed Signals StDev of the Log of the processed Signals the CV of the processed signals The Median Log Proc Signal CV StDev of the Log of the processed signals all show up in the Agilent SpikelIns Signal Statistics table of the QC report For each sequence use the calculated Background SubtractedSignalAverage and compare against the StdDeviation of the Negative Controls StdDevBgSubSigNegCtrl using the formula BGSubAverage MultErrorGreen gt StdDevBgSubSigNegCtrl Exclude the Proc Signals that fail this test and use the median of the Proc Signals for the remaining sequences as the initial guess b Max is estimated as Log Scanner SaturationValue c x0 is estimated by starting with the y value max min 2 then finding the 2 closest Med Log Proc Signals above and below this point Finding the Log concentrations of those points and then computing a slope and an intercept by slope MedianLogProcSig HIGH MedianLogProcSig LOW LogConc HIGH LogConc LOW J intercept LogConc HIGH slope MedianLogProcSig HIGH d wis estimated by using the slope calculated above By looking at the derivative of F x at xO we get DF X x0 max min 4 w so w 4 slope max min e After the estimates are complete the data is fit and the parameters Min
6. reQCSig2BkgLow1 reQCSig2BkgLow2 rNegCtriNumInliers rNegCtrlAveNetSig Type integer float float float float integer float float float float float float integer float Description The number of saturated non control features NetSignal intensity at 99th percentile for all non control probes NetSignal intensity at 50th percentile for all non control probes NetSignal intensity at 1st percentile for all non control probes The median percent CV of background subtracted signals for inlier noncontrol probes The number of saturated spike in features NetSignal intensity at 99th percentile of all spike in probes NetSignal intensity at 50th percentile of all spike in probes NetSignal intensity at 1st percentile of all spike in probes The median percent CV of background subtracted signals for inlier spike in probes Median ratio net signal to BGUsed of all inlier features for an spike in probe with lowest concentration spiked in red and green channels Median ratio net signal to BGUsed of all inlier features for an spike in probe with second lowest concentration spiked in red and green channels Number of all inlier negative controls Average net signal of all inlier negative controls Feature Extraction for CytoGenomics Reference Guide Table 7 Stats results contained in the text output file STATS table continued Stats Green Channel gNegCtrlSDevNetSig
7. Note that this equation is valid only if there is no background subtraction spatial detrending is on and there is no global background adjustment For an explanation of BGUsed with other background settings see rBGSubSignal rMeanSignal rGBGUsed Table 20 on page 190 13430 2 13502 52 72 2993 Results from Correct Dye Biases Algorithm Refer to Data from the STATS Table on page 221 for the FeatureNum gDyeNormSignal rDyeNormSignal LinearDyeNormFactor value 12519 45834 1 49209 6 rDyeNormSignal rBGSubSignal x rLinearDyeNormFactor x rhOWESSDyeNormFactor 49209 6 13430 2 x 4 14607 x rLOWESSDyeNormFactor 222 Feature Extraction for CytoGenomics Reference Guide Results from Compute Ratios and Errors Algorithm FeatureNum gSurrogateUsed rSurrogateUsed gProcessedSignal rProcessedSignal 12519 0 0 45834 13 49209 64 FeatureNum LogRatio LogRatioError PValueLogRatio 12519 0 0308611696 0 06148592089 0 6157220099 For the red channel does the feature number 12519 pass the two criteria listed below that are required to calculate an accurate and reproducible log ratio e Feature is positive and significant vs background i e IsPosAndSignif 1 e BGSubSignal is greater than its background standard deviation i e BGSDUsed For this example calculation feature number 12519 passed both criteria Since rSurrogateUsed 0 the rDyeNormSignal is the same value as the rProcessedSignal rProcessedSignal rDyeNormSi
8. FeaturesInNegativeControlRange background detrend option Specifies to remove negative control features that are outliers before calculating the negative control spread for use with FeaturesInNegativeControlRange Determines which features are considered for the surface fit set All inlier features Negative control inliers only Features in negative control range Feature Extraction for CytoGenomics Reference Guide Table 3 List of parameters and options contained within the FULL text output file FEPARAMS table Protocol Step Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Parameters BGSubtractor_DetrendNeighborhood Size BGSubtractor_ErrModelSignificance BGSubtractor_RobustNCStats BGSubtractor_RobustNCOutlierFactor BGSubtractor_ErrorModel BGSubtractor_MultErrorGreen BGSubtractor_MultErrorRed Type Options float integer 0 pixel statistics 1 error model integer 1 True 0 False float integer 2 0 float float Description Specifies the fraction of total number of neighborhood data points that will be weighted for linear regression during surface fitting for each data point Decides whether the error model or pixel staistics are used to determine Positive and Significance calls
9. If there are no stats for non control probes Feature Extraction looks at the spike in control probes If the CVs for these become worse Feature Extraction removes detrending If the option Detrend on Replicates only is chosen and if there are not enough replicates for non control or spike in control probes Feature Extraction turns off multiplicative detrending Feature Extraction for CytoGenomics Reference Guide 37 38 Spatial Distribution of Significantly Up Regulated and Down Regulated Features Positive and Negative Log Ratios You can display the distribution of the significantly up and down regulated features on this plot up red down green Spatial Distribution of Significantly Up Regulated and Down Regulated Features 3 7 z Si RE Figure 15 QC Report Spatial Distribution of Up and Down Regulated Features For the CGH QC Report this plot is referred to as Spatial Distribution of the Positive and Negative Log Ratios If the microarray contains greater than 5000 features the software randomly selects 5000 data points These points include the number of up regulated features in the same proportion to the number of down regulated features as they are found on the actual microarray The threshold that is used to determine significance is set in the protocol QCMetrics_differentialExpressionPValue These are the same features shown as up or down regulated in Figure 16 Feature Extr
10. gNegCtrlAveBGSubSig gNegCtriSDevBGSubSig gAveNumPixOLLo gAveNumPixOLHi gPixCVofHighSignalFeat gNumHighSignalFeat NonCtrlAbsAveLogRatio NonCtrlSDevLogRatio NonCtrlSNRLogRatio Stats Red Channel rNegCtriSDevNetSig rNegCtrl AveBGSubSig rNegCtriSDevBGSubSig rAveNumPixOLLo rAveNumPixOLHi rPixCVofHighSignalFeat rNumHighSignalFeat Type float float float integer integer float integer float float float Description Standard deviation of the net signal of all inlier negative controls Average background subtracted signal of all inlier negative controls Standard deviation of the background subtracted signals of all inlier negative controls The average number of pixels that are rejected from each feature at the low end of the intensity spectrum The average number of pixels that are rejected from each feature at the high end of the intensity spectrum Average of pixel CV for features with high signal The number of features with high signal This result is from a two step calculation Step 1 for each probe calculates the absolute average log ratio of all inlier non control features with minimum number of replicates Step 2 calculates the average of all absolute average log ratios calculated in step 1 The average standard deviation of log ratios of all inlier non control probe sets with a minimum number of replicates The average of signal to noise values of the l
11. Feature Extraction for CytoGenomics Reference Guide Default Setting Value v10 10 Hidden if Array Format is set to Automatically Determine 0 300 All Formats except Third Party Hidden if Array Format is set to Automatically Determine 5 All Formats except Third Party Hidden if Array Format is set to Automatically Determine 0 200 All Formats except Third Party Hidden if Array Format is set to Automatically Determine 20 All Formats except Third Party Automatically Determine Recognized formats Single Density 11k 22k 25k Double Density 44k 95k 185k 185k 10 uM 244k 10uM 65 micron feature size 30 micron feature size and Third Party Hidden if Array Format is set to Automatically Determine True All Formats Hidden if Array Format is set to Automatically Determine 8 0 for all formats except for third party for which it is set to 1 5 Hidden if Array Format is set to Automatically Determine Use Cookie All Formats Hidden if Array Format is set to Automatically Determine 0 650 Single Density 25k 0 561 Double Density 95k 15 Table 1 Default settings for the preloaded CGH protocols Protocol Step Parameter Exclusion Zone Percentage Auto Estimate the Local Radius LocalBGRadius Pixel Outlier Rejection Method RejectlORFeat RejectlORBG Statistical Method for Spot Values from Pixels Flag Outliers Compute Population Outliers Minimum Population Default S
12. Features Red rDyeNormSignal rDyeNormError rSpatialDetrendlsIn FilteredSet rSpatialDetrend SurfaceValue rlsLlowEnoughAdd Detrend Types float float float float boolean float boolean float float Options 0 Propagated model chosen by you or by software 1 Universal error model chosen by you or by software 1 Feature in filtered set 0 Feature notin filtered set Description The dye normalized signal in the indicated channel The standard error associated with the dye normalized signal Dye normalized red and green pixel correlation Indicates the error model that you chose for Feature Extraction or that the software uses if you have chosen the Most Conservative option A signal to noise parameter used to calculate pValue calculated differently depending on error model chosen Set to true for a given feature if it is part of the filtered set used to detrend the background This feature is considered part of the locally weighted lowest x of features as defined by the DetrendLowPassPercentage Value of the smoothed surface calculated by the Spatial detrend algorithm These points are considered to be in the background for the purposes of spatial detrending and multiplicative detrending If the Boolean value is true for a given point it will be used in spatial detrending and not in multiplicative detrending depends on parameters Diameter of the spot X axi
13. The same algorithm is used to calculate the Median CV for the spike in probes as well Because there are only 10 sequences in total and some are expected to fail the Additive error test described above the minimum number of bright enough sequences required to calculate the Median CV is 3 Feature Extraction for CytoGenomics Reference Guide 43 44 Microarray Uniformity 2 color only The QC Report has two metrics that measure the uniformity of replicated log ratios and that indicate the span of log ratios average S N and AbsAvgLogRatio These are calculated from inlier features of replicated non control and spike in probes For example some microarrays have 100 different non control probe sequences with 10 replicate features each For each replicate probe the average and SD of the log ratios are calculated The signal to noise S N of the log ratio for each probe is calculated as the absolute of the average of the log ratios divided by the SD of the log ratios From the population of 100 S N s for example the average S N is determined and shown in the table below The second metric AbsAvgLogRatio indicates the amount of differential expression up regulated or down regulated As described above averages of log ratios are calculated for each replicated probe The absolute of these averages is determined next Then the average of these absolute of averages is calculated to get a single value for the QC Report The la
14. Time stamp at the beginning of Feature Extraction FeatureExtractor UserName text Windows Log In Name of the User who ran Feature Extraction FeatureExtractor_ ComputerName text Computer name on which Feature Extraction was run FeatureExtractor Version text Version of Feature Extractor FeatureExtractor_IsXDRExtraction integer Says if result is from an XDR extraction 1 True 0 False Feature Extraction for CytoGenomics Reference Guide 93 Table 5 List of parameters and options contained within the QC text output file FEPARAMS table Protocol Step 94 Parameters FeatureExtractor_ColorMode FeatureExtractor QCReportlype DyeNorm_NormFilename DyeNorm_NormNumProbes Grid_IsGridFile Type Options Description integer A flag to indicate output color 0 One color green only 1 2 color integer Type of OC report to generate 0 Gene Expression 1 CGH_ChIP 2 miRNA 4 Streamlined CGH text Name of the dye normalization list file integer Number of probes in the dye normalization list boolean Indicates whether the grid is from a grid file Feature Extraction for CytoGenomics Reference Guide MINIMAL FEPARAMS Table Table 6 List of parameters and options contained within the MINIMAL text output file FEPARAMS table Protocol Step Parameters Protocol Name Protocol date Scan_ScannerName Scan_NumChannels Scan_date Scan_MicronsPerPixelX Scan_MicronsPerPixelY Scan_OriginalGUID Scan_NumScanPass Gr
15. and WellAboveBackground Specifies if a variation in the population algorithm is turned on This algorithm repeats the population outlier IQR algorithm on all features classified as negative controls after the first pass of population algorithm has been run on each sequence You may want to use this algorithm when you see hot features that have not been flagged as population outliers or hot sequences where all features of the sequence have higher signals than those in other negative control sequences To calculate robust IQR statistics the algorithm uses upper and lower limits that contain a Multiplier x IQR term This parameter is the Multiplier Choose universal error or the most conservative Universal Error Model Most Conservative Multiplicative error component in Green channel Multiplicative error component in Red channel Feature Extraction for CytoGenomics Reference Guide 83 Table 3 List of parameters and options contained within the FULL text output file FEPARAMS table Protocol Step Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Parameters BGSubtractor_AutoEstimateAddErrorG reen BGSubtractor_AutoEstimateAddErrorR ed BGSubtractor_AddErrorGreen BG
16. and the plot is linear Figure 48 Feature Extraction for CytoGenomics Reference Guide 199 50000 10000 5000 1000 500 100 50 rBGSubSignal 1 10 100 1000 10000 gBGSubSignal Figure 48 Adjusted background subtracted signals The bias if uncorrected yields a log ratio versus signal plot that is not symmetric about the log ratio axis Figure 49 whereas after adjustment the data is more symmetric Figure 50 LogRatio ri rae Girya 2 de po 50 100 500 1000 5000 10000 500001 0000200000 Avq qrProcessed Siqnal Figure 49 Log ratios calculated from unadjusted background subtracted signals 200 Feature Extraction for CytoGenomics Reference Guide LogRatio 50 100 500 1000 5000 10000 500001 000000000 Avg_grProcessed_Signal Figure 50 Log ratios calculated from adjusted background subtracted signals How is the Adjust background globally pad used If Adjust background globally is selected you can enter a constant between 0 and 500 called the pad value which forces the log ratio of red green towards zero The value of the pad is expressed in raw counts before dye normalization The Feature Extraction program assumes that this value applies to the red or green channel with the smallest mean signal and automatically computes the corresponding raw value in the other channel that would yield a corrected log ratio of zero after dye normalization The red and green feature signals are a
17. average of signals This calculation is done for each replicated probe and the median of those CV s is reported in the table for each channel SNP probes are not included Feature Extraction for CytoGenomics Reference Guide Reproducibility YCV for Replicated Probes Median CV Signal inliers Non Control probes Red Green Red Green Agilent SpikeIns BGSubSignal 15 05 13 48 10 21 10 57 ProcessedSignal 7 39 7 75 4 44 5 54 Figure 19 QC Report Reproducibility A lower median CV value indicates better reproducibility of signal across the microarray than a higher value Exclusion of dim probes Feature Extraction calculates the Median CV using those probes bright enough to be in the range where the noise is more proportional to signal Feature Extraction excludes from the calculation any sequences for which the Average BGSubSignal x Multiplicative error lt Additive error Dye Norm Factor For 1 color data the Dye Norm Factor is 1 A probe sequence will have a CV calculated if the number of features that pass the filters NonUniform and signal filter described above is greater than the minimum replicate number indicated in the protocol Q CMetrics_minReplicatePopulation If the number of replicated sequences with enough inlier features is less than 10 or less than 10 of the replicated sequence that is if there are not enough bright replicated probes the Median CV field shows up as 1 Spike in probes
18. channel they do not use this protocol step Calculate Metrics These algorithms calculate all the QC metrics for the analysis One of the primary algorithms in this step is the gridding test whose parameter values are hidden in the protocol This algorithm yields grid warnings on the Summary Reports and the Evaluate Grid warning in the QC Report Agilent has added many more tests to assess if gridding has been successful or not Protocols for Agilent arrays also have associated QC metric sets These metrics are calculated at this step Generate Results This part of the process generates the output result files using the parameter values specified in the protocol step and the selections made in the Project Properties window This step is not discussed in this chapter Feature Extraction for CytoGenomics Reference Guide 165 Algorithms and results they produce The table below summarizes the results for each algorithm protocol step These result names are used in the equations for the calculations for each algorithm Table 18 Algorithms Protocol Steps and the results they produce Protocol Step Results Result Definition Find Spots MeanSignal Average raw signal of feature calculated from the intensities of all inlier pixels that represent the feature after outlier pixel rejection The number of inlier pixels is shown in the column NumPix Find Spots MedianSignal Median raw signal of feature calculated from the intens
19. data into GeneSpring the pattern information can be obtained from within the Feature Extraction profile tab text file or can be obtained by download from the GeneSpring Web site Feature Extraction for CytoGenomics Reference Guide MAGE ML results Ditferences between MAGE ML and text result files The MAGE ML result file includes most of the same parameters statistics and results as the FULL text result file with the following differences e Scanner control parameters are included in the file e Some Feature Extraction parameter names FE PARAMS table have been changed to accommodate Rosetta Resolver terminology e MAGE result file includes all information included in the FEATURES table except for annotations deletion control information and spot size information e Feature results FEATURES table are associated with quantitation types as defined by the Object Management Group in its Gene Expression Specification paper of February 2003 V 1 These types are listed below Measured Signal Derived Signal Ratio Confidence Indicators error and p value Specialized Quantitation Type SQT includes all other data Full and Compact Output Packages In the Properties sheet for the project you can select if you want the MAGE ML result file to contain all the possible columns and results Full or a reduced set of results Compact MAGE ML files can also be compressed before they are sent via FTP Compressed MAGE ML fi
20. deviation and then squares it to yield the pixel variance e From a histogram plot of number of features or bkgd vs net signal finds the net signal value for the 25th percentile Feature Extraction for CytoGenomics Reference Guide 185 186 e From a histogram plot of number of feature or local bkgd vs variance finds the variance for the 25th percentile e Calculates the B term as 25 NetSignal X B Term Multiplier and the C term as 25 Variance X C Term Multiplier For a given scanner multipliers need to be determined This tuning should use many images from different batches of microarrays different users and different processes Different channels may need their own multipliers Measured Feature or Background Variance o M n li x gt x 9 where n is of inlier pixels in the feature or background i e NumPix or BGNumPix respectively where X is raw pixel intensity in the feature or background Cinlier pixels where X is mean raw pixel intensity for the feature or background i e MeanSignal or BGMeanSignal respectively Step 11 Determine if the feature is a population outlier IsFeatPopOL Agilent provides two different statistical algorithms for identifying population outliers You select the appropriate algorithm to use in the protocol For probe sequences with enough replicate features Feature Extraction uses the IQR test for population outlier analysis The minimum number of replicates
21. feature Standard Deviation in Red Green space The covariance of two features measures their tendency to vary together i e to co vary In this case it is a cumulative quantitation of the tendency of pixels belonging to a particular feature in Red and Green spaces to co vary float BGPixCorrelation The same concept as above but in case of background SOT glsFeatNonUnifOL rlsFeatNonUnifOL g r lsFeatNonUnifOL Integer indicating if a feature is a 1 indicates Feature NonUniformity Outlier or not A feature is a non uniformity is non uniform if the pixel noise of outlier in g r feature exceeds a threshold established for a uniform feature SOT glsBGNonUnifOL rlsBGNonUnifOL g r isBGNonUnifOL The same concept as above but for 1 indicates Local background background is a non uniformity outlier in g r Feature Extraction for CytoGenomics Reference Guide 149 Table 15 Feature results Full contained in the MAGE ML FEATURES table Quant Features Green Features Red Options Description Type SQT glsFeatPopnOL rlsFeatPopnOL g r lsFeatPopnOL 1 Boolean flag indicating if a feature is a indicates Feature isa Population Outlier or not Probes with population outlier in replicate features on a microarray are g r examined using population statistics A feature is a population outlier if its signal is less than a lower threshold or exceeds an upper threshold determined using a multiplier 1 42 times the interquartile ran
22. features N 3 0 970 4 0 829 Feature Extraction for CytoGenomics Reference Guide 187 See Step 6 Reject outliers on page 181 for definitions to help you understand the Interquartile Range 188 Table 19 critical values at 95 confidence level continued Number of Ocritical replicated features N D 0 710 6 0 625 1 0 568 8 0 526 9 0 493 10 0 466 IQR Test for replicate features gt or minimum population number The equations below are calculated for each feature and background population per channel The intensities of all features or background regions in the population are plotted on a distribution curve The difference in intensities between the 25 and 75 percentiles represent the Interquartile Range IQR kt I0A72 8 1 42 10R AS A Boundary for rejection ole 50 ile J5 ile Boundary for rejection IO Figure 46 Interquartile Range Cutoff PopOutlier 1 A2 x I QR 10 Feature Extraction for CytoGenomics Reference Guide where IQR Intensity at 75h percentile Intensity at 25th percentile where 1 42 is the IQR factor Agilent uses 1 42 as the IQR factor so that the cutoff boundaries encompass 99 of the expected population distribution The user can change this factor to encompass different boundaries as discussed in the Agilent Feature Extraction for CytoGenomics User Guide Feature or background is flagged as population outlier e g IsFeatPopOL or IsSBGPopOL respectiv
23. fit of the negative controls It is equivalent to a standard deviation of NC signals after removal of spatial homogeneities Used as a preliminary estimation of the noise on the array for selecting near zero probes in spatial detrending and conversely for excluding near zero probes in multiplicative detrending Feature Extraction for CytoGenomics Reference Guide Table 7 Stats results contained in the text output file STATS table continued Stats Green Channel gNonCtriNumWellAboveBG rNonCtriNumWellAboveBG LogRatiolmbalance ImageDepth AFHold gPMTVolts rPMTVolts GlassThickness Feature Extraction for CytoGenomics Reference Guide Stats Red Channel Type integer float string float float float Description Measure of the number of noncontrol features whose signals are well above background Used as a metric for the number of features with significant signal This metric is for CGH only It calculates the amount of amplifications versus duplications per chromosome to determine if there is an imbalance that falls outside of normal expectations 16 bit or 20 bit The percentage of time during a scan that the Autofocus assembly holds its position rather than actively maintaining focus Typically the value is less than 2 however the value will be larger if there are obstructions on the microarray that interfere with the laser beams The voltages that Photomultipliers are set to The
24. for storing additional file information This tag points to a data structure This data structure is not public but information stored in the data structure is available to customers in the MATLAB file format This tag points to a string containing the file description The usual TIFF description tags tag 270 are used to hold the color name red or green for each image This allows programs that interpret only standard TIFF tags to determine image colors The Page Name tag tag 285 also contains the color names Feature Extraction for CytoGenomics Reference Guide Agilent CytoGenomics 3 0 Agilent Feature Extraction for CytoGenomics Reference Guide 5 How Algorithms Calculate Results Overview of Feature Extraction algorithms 160 XDR Extraction Process 170 How each algorithm calculates a result 174 Example calculations for feature 12519 of Agilent Human 22K image 220 This chapter shows you how each Feature Extraction algorithm uses its parameters to calculate results that are passed on to the next algorithm and finally on to third party data analysis programs fhe Agilent Technologies 159 Overview of Feature Extraction algorithms Protocol step algorithms operate similarly during the Feature Extraction process for 2 color gene expression CGH ChIP and non Agilent microarrays That is the algorithms and parameter fields are similar but the parameter values are different depending on the protocol
25. greater than 0 with a known additive error We compute the probability in a similar way to the Pixel Significance calculation But instead of having a feature signal and a background signal the test uses the feature signal and one error background signal distribution is assumed to be around 0 with one error The degrees of freedom are large enough to make the function Gaussian We define the error as one standard deviation 1SD from the probability of 0 on the Gaussian curve and equal to a p value of 01 AdditiveError 2 6 If the probability is greater than or equal to 1SD or 01 the background subtracted signal is flagged as positive and significant If it is less than 1SD or O1 it is flagged as not significant The value of the surrogate is scaled by the probability returned The surrogate value for the Not significant signals equals AddError 2 6 the probability calculated this way for two reasons e Signals stay continuous e Surrogate values are not larger than the smallest significant signals Feature Extraction for CytoGenomics Reference Guide Step 18 Determine if the feature background subtracted signal is well above the background IsWellAboveBG The feature background subtracted signal i e BGSubSignal is compared to the noise of its background local or global BGSubSignal gt WellAboveSDMulti x SDpgG where WellABoveSDMulti is the well above SD multiplier 5 default this means a feature is wel
26. in calculation of any CGH QC Metric 60 Feature Extraction for CytoGenomics Reference Guide CytoCGH OCMT 1x Mar14 Metric Set Info Created On 20 Mar 2014 11 01 Type Agilent Description Removable False Metrics Metric Name Excellent Good IsGoodGrid gt 1 NA AnyColorPrentFeatWonU lt 1 1lto5 DerivativeLR_Spread lt 0 20 0 20 to 0 30 gRepro 0 to 0 10 0 10 to 0 20 lt 0 or 0 20 g_EGMoise lt 8 8tol5 215 g_Signal2Notse gt 100 30 to 100 lt 30 g_Signallntensity 2150 50 to 150 lt 50 rRepro 0 to 0 10 0 10 to 0 20 lt 0 or 0 20 r_BGNoise lt 8 amp to1l5 gt 15 r Signal2Noise gt 100 30 to 100 lt 30 rSignallntensity 2150 50 to 150 lt 50 RestrictionControl 0 80 tol lt 0 80 or gt 1 LogRatiolmbalance 0 26 to 0 26 0 75 to 0 26 or 0 26 to 0 75 lt 0 75 or 0 75 Figure 30 QC Metrics for CytoCGH QCMT _1x_Mar14 metric set Feature Extraction for CytoGenomics Reference Guide CytoCGH OCMT 2x Mar14 PROM ROT NCE eR Ponce A A ni ey pe Nel po eC Ne a A Oo ih ee Oe mock aT 3 205 eS eae Se i af if d j Far Properties CytolGH ORNI k UC F LE a Metric Set Info Created On 20 Mar 2014 11 01 Type Agilent Description Removable False Metric Name Excellent Good Evaluate IsGoodGrid gt 1 MA AnyColorPrentFeatNonU lt 1 lto5 DerivativeLR_Spread 0 20 0 20 to 0 30 gRepro Oto 0 10 0 10 to 0 20 0 or gt 0 20 g_BGNotse 10 10 to 20 gt 20 g_Signal2Noise 100 50 to 100 lt 50 g_Signalln
27. minimum number of replicates for population outliers is greater than 2 and less than the minimum population specified in the outlier section of the protocol Indicates whether to report population outliers as Failed in MAGEML output Enables multiplicative detrending 1 color and CGH microarray protocols have this parameter enabled No filtering Average filtering Median filtering The increment in number of features by which the square window Is shifted horizontally and vertically on the microarray Specifies size of the square window by the number of rows and columns The specified percentage of low intensity features is selected from this window size Specifies the fraction of total number of neighborhood data points that will be weighted for linear regression during surface fitting for each data point 79 Table 3 Protocol Step Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Parameters BGSubtractor_MultHighPassFilter BGSubtractor_PolynomialMultipli cativeDetrend BGSubtractor_NegCtrlThresholdMultD etrendFactor BGSubtractor_PolynomialMulti plicativeDetrendDegree BGSubtractor_TestMultDetrendOnCVs BGSubtractor_MultDetrendOn Replicates Type Options integer 1 True 0 False integer 1 True 0 False float integer 1 5
28. needed is set by the protocol field Minimum Population and is set to 10 as the default for most Agilent protocols Feature Extraction for CytoGenomics Reference Guide If the protocol choice Use Qtest for Small Populations is set to True the Q test method is used when a probe sequence has fewer than the minimum population number of features The Q test choice is set to True for Agilent s newer protocols Otest for replicate features lt minimum population number Q test allows population outlier flagging for probe sequences from one less than the minimum population number down to 3 This test is especially useful for NegC probes on CGH microarrays Flagging features as population outliers is needed to accurately calculate NegCAvg and SD statistics This algorithm uses the following equation Qi Xi Xnearest Xmax Xmin Where Xi the intensity of a probe sequence Xnearest the intensity of the nearest probe sequence in intensity Xmax the intensity of the most intense probe sequence Xmin the intensity of the least intense probe sequence Qi is compared to Qcritical to determine if the feature is an outlier Qcritical depends upon the number of replicate features N and upon the chosen confidence level Agilent has chosen a 95 confidence level and bases the identification of population outliers on this table Table 19 Qcritical values at 95 confidence level Number of Ocritical replicated
29. rank consistent The limit on the number of points used for the dye normalization set If the number is greater than this a random subset is chosen using this number of points Software excludes any features from the dye normalization set if the local backgrounds associated with those features have been flagged as population outliers in either channel The default recommendation is False Version of Ratio algorithm Both positive and negative log ratio values are capped to this absolute value Use Spikelns Do not use Spikelns Minimum number of replicates necessary to calculate replicate statistics The pValue to use to look for differentially expressed genes 86 Feature Extraction for CytoGenomics Reference Guide Table 3 List of parameters and options contained within the FULL text output file FEPARAMS table Protocol Step Calculate Metrics Calculate Metrics Calculate Metrics Calculate Metrics Calculate Metrics Calculate Metrics Calculate Metrics Calculate Metrics Feature Extraction for CytoGenomics Reference Guide Parameters OCMetrics_MaxEdgeDefect Threshold OCMetrics_MaxEdgeNotFound Threshold OCMetrics_ MaxLocalBGNonUnif Threshold OCMetrics_MinNegCtrlSDev OCMetrics_ MinReproducibility OQCMetrics_Formulation OCMetrics_ EnableDyeFlip OQCMetrics_PercentileValuefor Signal FeatureExtractor_Version Type Options float float float float float int
30. representing an estimate of the scanner offset 184 Step 10 Determine if the feature is a non uniformity outlier IsFeatNonUnifOL The non uniformity outlier algorithm flags anomalous features and local backgrounds based on statistical deviations from the Agilent noise model Feature or background is flagged as a non uniformity outlier e g IsFeatNonUnifOL or IsBGNonUnifOL respectively if the measured variance is greater than the product of the estumated variance and the confidence interval multiplier oy Sh op x CI Where CI is the confidence interval calculated from chi square distribution The equations below are calculated for each feature and background per channel Estimated Feature or Background Variance The Agilent noise model estimates the expected variance by using noise effects from the Agilent Microarray Gene Expression system which includes microarray manufacture wet lab chemistry and scanner noise 2 2 2 2 O k 0 Labeling FeatureSynthesis O Counting Noise 6 op Ax Bx C 7 x is the net signal of feature or background A or o Labeling FeatureSynthesis 18 the term that estimates the sources of variance that are proportional to the square of the signal including microarray manufacturing and wet chemistry effects the variance follows a Gaussian distribution This term is intensity dependent and is the square of the CV e g coefficient of variation estimate of the pixel noise Feature Extraction
31. that affect the process and results for Feature Extraction Parameter values in the protocol depend on the microarray type and your experiment The following pages list the default settings for each of the protocol templates shipped or downloaded with the software Each protocol template represents a different microarray type You can display these settings and values when you open the Protocol Editor for each of the protocol templates fhe Agilent Technologies 11 Default Protocol Settings Introduction To learn more about changing the This chapter presents tables for display of the default default values for the protocols settings for each protocol Parameter values depend on see the Agilent Feature Extraction e microarray type for CytoGenomics User Guide e lab protocol e formats e scanner used To learn about the naming of the protocol templates see the Agilent Feature Extraction for CytoGenomics User Guide 12 Feature Extraction for CytoGenomics Reference Guide Default Protocol Settings CAUTION These protocol settings may not be optimal for non Agilent microarrays or Agilent microarrays processed with non Agilent procedures You must determine the settings and values that are optimal for your system CytoCGH 0209 1x _Mar14 CytoCGH 0209 2x Mar14 CytoCGH 0209 4x Mar14 CytoCGH 0209 8x Mar14 CytoCGH 0300 SingleCell Nov14 These are CGH protocols for use with the Oligonucleotide Array Based CGH for Genomic D
32. the 1 color QC Report Log of high signal in the linear range of curve fit Agilent Spike In Concentration Response Statistic in the 1 color QC Report Slope of the linear range of curve fit Agilent Spike In Concentration Response Statistic in the 1 color QC Report Intercept of the linear range of curve fit Agilent Spike In Concentration Response Statistic in the 1 color QC Report Square of the correlation coefficient of the linear range of curve fit The detection limit as determined by measuring the average plus 1 standard deviation of all spike in probes below the linear concentration range This value is the maximum of these Background subtracted signal intensity at 50th percentile for all non control probes The median background subtracted signal for all the embedded QC probes on the microarray 107 Table 7 Stats results contained in the text output file STATS table continued Stats Green Channel gMedPrentCVProcSignal geQCMedPrentCVProcSignal gOutlierFlagger_Auto_FeatB Term gOutlierFlagger_Auto_FeatC Term gOutlierFlagger_Auto_BgndB Term 108 Stats Red Channel rMedPrentCVProcSignal reQCMedPrentCVProcSignal rOutlierFlagger_Auto_FeatB Term rOutlierFlagger_Auto_FeatC Term rOutlierFlagger_Auto_BgndB Term Type float float float float float Description The median CV for replicate non control probes using the processed signal This value is calculated by c
33. the data sets the chip and hybe access controls in Rosetta Resolver before importing the profile scan data For autoimport the profile is normally placed in the MAGE directory XML Control Type output If a feature is used in dye normalization its Control_Type is normalization even though it can also be a positive or negative control If a feature is not used in normalization it is either positive negative deletion mismatch or false 156 Feature Extraction for CytoGenomics Reference Guide Table 17 Control Type Definitions Name XML Probe false Positive Control pos or positive Negative Control neg or negative Not Probe notprobe Not Probe These features are feature extracted but they are not used by Feature Extraction as input to any calculations these features are not used during outlier analysis or for the dye normalization calculation However dye normalization values and ratios are calculated and the results appear in the text and XML output files and the feature extraction visual results file An exception is that Not Probe s background is used in the calculation of the local background with the radius method Conversion of feature flag information Failed MAGE ML produce the following settings Bit 8 green and 12 red are set if the feature is saturated in both channels Bit 18 is set if the feature or its deletion control is a non uniformity outlier in either color or if the feature is a p
34. to 0 20 lt 15 gt 10 gt 30 0 10 to 0 20 lt 15 gt 8 gt 25 Evaluate lt 1 25 gt O 70 lt or gt 0 20 gt 15 lt 10 lt 30 lt 0 or 0 20 gt 15 lt 8 lt 25 QC Metrics for CytoCGH_OQCMT_ SingleCell_ Nov14 metric set 65 Metric Evaluation Logic For details on how to associate a QC metric set with a protocol see the Feature Extraction for CytoGenomics User Guide 66 When a QC metric set is associated with a protocol it is used to evaluate results using up to three defined threshold values for given metrics Results are then flagged in the QC Report Evaluation Metrics table according to the logic described in the following diagram and tables Figure 35 shows the metric evaluation using three threshold levels The black dots indicate how a result is evaluated if its value is the same as a limit value Good Upper warning limit Good Lower limit Figure 35 Three level QC Metrics evaluation used for Feature Extraction The following tables describe how results are evaluated using up to three threshold levels Metric Evaluation Logic tables In the following tables evaluation metrics are described for 18 cases IDs Results are compared to four limit values shown in the Limits used table upper limit upper warning limit lower warning limit and lower limit v1 through v4 The logic used is described in the center table showing the metric evaluation indicatio
35. you can distinguish a low frequency trend outside of the high frequency noise 40 The first of these graphs plots the median Processed Signal and median BGSub Signal for each row over all columns of a 1 color GE microarray The second plots the same signals for each column over all rows of the 1 color GE microarray The difference between the Processed Signal and the BGSubSignal represents the effect of the multiplicative detrending The Processed Signal should look flatter Spatial Distribution of Median Signals for each Row Median Signal 0 1 51 101 151 201 251 301 351 401 451 501 Row E Median BGSub Signal for Row Median Proc Signal for Row Spatial Distribution of Median Signals for each Column Median Signal 31 41 51 61 71 61 Column Median BGSub Signal for Column Median Proc Signal for Column Figure 17 1 color QC Report Median Signal Spatial Distribution Feature Extraction for CytoGenomics Reference Guide Histogram of LogRatio plot This is a plot of the log ratio distributions and displays the log ratios vs the number of probes This plot is included only in the CGH_ChIP report which is the default report for the ChIP_1010_Sep10 protocol Histogram of LogRatio g 5 i iD Fz 5 Le ao a 5 LL D Fr E a 2000 1000 0 25 20 15 10 05 00 05 10 15 20 Log Ratio Figure 18 Histogram of LogRatio plot Feature Extraction for CytoGenomics Reference Guide 41 Inter Fea
36. 0 01 20 BG Method No Background Image Hu22K_GE2_251209710036 Background Detrend On FeatNCRange LoPass Protocol GE2_1010_Sepi0 Read Only Multiplicative Detrend True Linear Lowess User Name Administrator Dye Norm Grid 012097_D_20070820 Linear DyeNorm Factor 4 15 Red 15 9 Green FE Version 10 10 0 23 Additive Error 14 Red 65 Green Sample red green Saturation Value 65211 r 65185 g DyeNorm List No of Probes in DyeNorm List Evaluation Metrics for GE2_QCMT_Sep10 Good 12 Figure 3 Metric Name IsGoodGrid AnyColorPrcntFeatNonun gNegCtrlAveBGSubSig gNegCtriSDevBGSubSig rNegCtriAveBGSubSig rNegCtriSDevBGSubSig gNonCntriMedCVBkSubSig rNonCntriMedCVBkSubSig gE1laMedCVvBkSubSignal rElaMedCVBkSubSignal absE1aObsVsExpCorr absE1aObsVsExpSlope Excellent Good Evaluate Value Excellent Good gt i lt 1 20 to 10 lt 15 20 to 4 lt 6 O to 18 0 to 18 0 to 18 0 to 18 gt 0 86 gt 0 85 Evaluate lt 1 gt 1 lt 20 or gt 10 gt 15 lt 20 or gt 4 gt 6 lt 0 or gt 18 lt 0 or gt 18 lt 0 or gt 18 lt 0 or gt 18 lt 0 86 lt 0 85 Partial QC Report Header and Evaluation Metrics with GE2 metric set with thresholds added Default protocol settings Feature Extraction for CytoGenomics Reference Guide 25 OC metric set results Spatial and Multiplicative Detrending Off Figure 4 is an example of a QC report header and Evaluation Metrics table gen
37. 025 BG NonUniform BG Population Red FeaturePopulation Red Feature MonUniform Green FeaturePopulation Green Feature NonUniform Figure 7 QC Report Number and Spatial Distribution of Outliers The number and percentage of features that are feature nonuniformity outliers in either the green or red channel is shown below the plot The 1 color report shows only the percentage of green feature non uniformity outliers Also the number and percentage of genes that are nonuniformity outliers in either channel is shown below the plot If there were replicate features representing one gene and at least one feature was not an outlier no gene outliers would appear Feature Extraction for CytoGenomics Reference Guide Net Signal Statistics Net signal is the mean signal Net signal statistics are an indication of the dynamic range minus the scanner offset Net of the signal on a microarray for both non control probes signal is used so that these and spike in probes not applicable for CGH QC report The Statistics are independent of the QC Report uses the range from the Ist percentile to the 99th scanner version percentile as an indicator of dynamic range for that microarray NetSignal is also a column in the FeatureData output For example in the figure below for non control probes the dynamic range of the net signal intensity for the red channel is from 42 to 6803 with half the probes having a net signal intensity of greate
38. 1 Indicates if grid has been adjusted for better fit as result of performing the interactively adjust corners method This is put out only if a metric set has been run It gives a status of the overall array If the Extraction Status 0 the output says ExtractionInRange If the Extraction Status 1 the output says ExtractionEvaluate Variance measure of whether or not positive Log Ratios appear to be correlated with position on the array Variance measure of whether or not negative Log Ratios appear to be correlated with position on the array StDev measure of whether or not positive Log Ratios appear to be correlated with position on the array StDev measure of whether or not negative Log Ratios appear to be correlated with position on the array Feature Extraction for CytoGenomics Reference Guide Table 7 Stats results contained in the text output file STATS table continued Stats Green Channel Stats Red Channel Type Description Metric_MetricName Optional Only displayed when a metric set is used The name of a metric in the metric set The given value is the one that has been calculated for this metric You can have more than one metric in a given metric set Metric _MetricName_IsInRange integer Optional Only displayed when a metric 1 in set is used Indicates whether the metric range was within any user defined thresholds 0 out of found in the metric set for that metric range Results are r
39. 1 42 times the interquartile range i e IQR of the population The same concept as above but for background Flags features for downstream filtering in third party gene expression software Background subtracted signal To display the values used to calculate this variable using different background signals and settings of spatial detrend and global background adjust see Table 20 on page 190 Boolean flag established via a 2 sided t test indicates if the mean signal of a feature is greater than the corresponding background selected by user and if this difference is significant To display variables used in the t test see lable 20 on page 190 127 Table9 Feature results contained in the COMPACT output text file COMPACT FEATURES table continued Features Green Features Red glsWellAboveBG rlsWellAboveBG SpotExtentX gBGMeanSignal rBGMeanSignal Description Boolean flag indicating if a feature is WellAbove Background or not feature passes g r lsPosAndSignif and additionally the g r BGSubSignal is greater than 2 6 g r BG_SD You can change the multiplier 2 6 Diameter of the spot X axis Mean local background signal local to corresponding feature computed per channel inlier pixels Results are reported to 9 decimal places in exponential notation for all result files 128 Feature Extraction for CytoGenomics Reference Guide QC Features Table Table 10 Feature results contained in th
40. 1000 Description per feature log of rProcessedSignal gProcessedSignal If SURROGATES are turned off then if DyeNormRedSig lt 0 0 amp DyeNormGreenSig gt 0 0 if DyeNormRedSig gt 0 0 amp DyeNormGreenSig lt 0 0 if DyeNormRedSig lt 0 0 amp DyeNormGreenSig lt 0 0 If SURROGATES are turned off then if DyeNormRedSig lt 0 0 OR DyeNormGreenSig lt 0 0 IF SURROGATES are turned on then LogRatioError error of the log ratio calculated according to the error model chosen Significance level of the LogRatio computed for a feature The signal left after all the Feature Extraction processing steps have been completed In the case of one color ProcesssedSignal contains the Multiplicatively Detrended BackgroundSubtracted Signal if the detrending is selected and helps If the detrending does not help this column will contain the BackgroundSubtractedSignal Feature Extraction for CytoGenomics Reference Guide Table 10 Feature results contained in the QC output text file QC FEATURES table Features Green Features Red Types Options gProcessedSigError rProcessedSigError float gNumPixOLHi rNumPixOLHi integer gNumPixOLLo rNumPixOLLo integer gNumPix rNumPix integer gMeanSignal rMeanSignal float gMedianSignal rMedianSignal float Feature Extraction for CytoGenomics Reference Guide Description The universal or propagated error left after all the processing steps of Feature Extractio
41. 3000000 2000000 Frequency Red 1000000 Frequency Green Figure 38 Zoomed in section of Figure 37 The background peaks are at 32 for the red channel and 50 for the green channel 6000000 5000000 4000000 3000000 2000000 1000000 Frequency Red Frequency Green o 5000 10000 15000 20000 25000 30000 35000 Figure 39 Histogram of a 30 micron feature array image after Back ground Peak Shifting Feature Extraction for CytoGenomics Reference Guide 175 6000000 4000000 Frequency Red 2000000 Frequency Green 0 0 20 40 60 80 100 120 Figure 40 Zoomed in section of Figure 39 Note the peaks at pixel val ue 0 Also note the dips in the frequency of values near the pixel value of 32 for the red channel and 50 for the green channel When the Use central part of pack for slope and skew calculation flag is set to True the gridding algorithm is modified to use central region of the pack to obtain slope skew and origin of each pack instead of using the edges of packs This enables the algorithm to correctly place the grid for arrays that have edges populated with dim spots When the Use the correlation method to obtain origin X of subgrids is set to False results obtained from the projection data analysis are used to estimate the origin Selecting this option will use the same calculations used in Feature Extraction version 10 7 10 9 or
42. 9 text file output 69 Rosetta Biosoftware use of XML output with 156 226 S signals background subtracted adjusted 200 background subtracted unadjusted 199 statistical results 98 T tables FEPARAMS 71 parameters 71 statistical results 98 text file feature results 114 parameters 69 statistical results 98 text file results 69 TIFF file format options 158 TIFF results 158 U up and down regulated features spatial distribution 38 Feature Extraction for CytoGenomics Reference Guide www agilent com In This Book The Reference Guide presents descriptions of the protocols or methods available for use with Agilent Feature Extraction for CytoGenomics as well as a listing of results and an explanation of how the Feature Extraction algorithms work This guide provides e alist of the default settings for each protocol shipped or downloaded with the software a list of all the parameters and results available after feature extraction e the equations and a sample calculation for the feature extraction process Agilent Technologies Inc 2015 Revision A1 August 2015 G1662 90045 fhe Agilent Technologies
43. A No of Probes in DyeNorm List NA u p Spot Finding of the Four Corners of the Arra Evaluation Metrics for CGH_QCMT_Sep10 4 2 Spot Finding of Four 2 Excellent 9 Good 2 i j s Metric Name Value Excellent Good Evaluate Corners on page 28 CrS Pofa IsGoodGrid 1 00 gt 1 NA lt 1 mi r sr AnyColorPrentFeatNonUn 0 01 lt 1 itos 5 D a DerivativeLR_Spread 0 18 lt 0 20 0 20 to 0 30 gt 0 30 gRepro 0 07 Oto 0 05 0 05 to 0 20 lt 0 or gt 0 20 3 Spatial Distribution of All tou a_BGNoise 1 67 lt 5 Stois gt 15 ii g_Signal2Noise 112 27 gt 100 30 to 100 lt 30 A SignalInten sit 187 79 gt 150 50 to 150 lt 50 Outliers on page 29 Grid Normal ae i 0 08 Oto 0 05 0 05to 0 20 lt 0 or gt 0 20 Outlier Numbers with Spatial Distribution r_BGNoise 2 33 lt 5 5to15 gt 15 3 534 rows x 456 columns r_Signal2Noise 135 01 gt 100 30to100 lt 30 r_SignalIntensity 314 95 gt 150 50 to 150 lt 50 4 QC reports with metric sets added on page 24 5 Histogram of Signals Plot on page 34 6 Red FeaturePopulation Red Feature NonUniform Log of BG SubSignal 6 0 li S ii 29 s Green FeaturePopulationg Green Feature N onUniform Histogram of Signals Plot Green ut ler tats on page Feature Red Green Any Outlier 10000 Non Uniform 19 18 23 0 01 9000 Population 114 129 214 0 09 8000 w 7000 o a 6000 5 5000 4000 E 2 3000 2000 1000 l rp ee oan re ee ee ail h ak ELE 0 1 2 3 Log of BG SubSignal 22 Figure 1 Feature Extractio
44. ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE DATA OR PROFITS WHETHER OR NOT ADVISED OF THE POSSIBILITY OF DAMAGE AND ON ANY THEORY OF LIABILITY ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE Feature Extraction for CytoGenomics Reference Guide Feature Extraction for CytoGenomics Reference Guide Content Default Protocol Settings Default Protocol Settings Introduction 12 Default Protocol Settings 13 CytoCGH_0209 1x_Mar14 CytoCGH_0209 2x Mar14 CytoCGH_0209 4x Mar14 CytoCGH_0209 8x_Mar14 CytoCGH 0300 SingleCell Novi4 13 OC Report Results QC Reports 22 Streamlined CGH QC Report 22 QC reports with metric sets added 24 QC Report Headers 27 Streamlined CGH QC Report 27 CGH ChIP QC Report 27 Feature Statistics 28 Spot Finding of Four Corners 28 Outlier Stats 29 Spatial Distribution of All Outliers 29 Net Signal Statistics 31 Negative Control Stats 32 Plot of Background Corrected Signals 33 Histogram of Signals Plot 34 Local Background Inliers 35 Foreground Surface Fit 35 Multiplicative Surface Fit 37 Spatial Distribution of Significantly Up Regulated and Down Regulated Features Positive and Negative Log Ratios 38 Feature Extraction for CytoGenomics Reference Guide 3 Plot of LogRatio vs Log ProcessedSignal 39 Spatial Distribution of Median Signals for each Row and Column 40 Histogram of LogRatio plot 41 Inter Feature Statistics 42 Reproducibility Statistics CV Replicat
45. Agilent CytoGenomics 3 0 Feature Extraction for CytoGenomics Reference Guide For Research Use Only Not for use in diagnostic procedures ofits Agilent Technologies Notices Agilent Technologies Inc 2015 No part of this manual may be reproduced in any form or by any means including elec tronic storage and retrieval or translation into a foreign language without prior agree ment and written consent from Agilent Technologies Inc as governed by United States and international copyright laws Manual Part Number 61662 90045 Edition Revision A1 August 2015 Printed in USA Agilent Technologies Inc 5301 Stevens Creek Blvd Santa Clara CA 95051 Agilent Recognized Trademarks Adobe the Adobe Logo Acrobat and the Acrobat Logo are trademarks of Adobe Systems Incorporated Pentium is a U S registered trademark of Intel Corporation Microsoft is a U S registered trademark of Microsoft Corporation Rosetta Luminator is a trademark of Rosetta Inpharmatics LLC Rosetta Resolver is a U S registered trademark of Rosetta Inpharmatics LLC Windows and MS Windows are U S registered trademarks of Microsoft Corpora tion Patents Portions of this product may be covered under US patent 6571005 licensed from the Regents of the University of California Warranty The material contained in this docu ment is provided as is and is sub ject to being changed without n
46. BGMedianSignal rBGPixSDev rlsSaturated rlsLowPMTScaled Up rlsFeatNonUnifOL rlsBGNonUnifOL Types float float float float boolean boolean float boolean boolean Options 1 Saturated or 0 Not saturated 1 Low 0 High g r lsFeatNonUnifO L 1 indicates Feature is a non uniformity outlier in g r g r IsBGNonUnifOL indicates Local background is a non uniformity Feature results contained in the OC output text file QC FEATURES table Description Standard deviation of all inlier pixels per feature this is computed independently in each channel Mean local background signal local to corresponding feature computed per channel inlier pixels Median local background signal local to corresponding feature computed per channel inlier pixels Standard deviation of all inlier pixels per local BG of each feature computed independently in each channel Boolean flag indicating if a feature is saturated or not A feature is saturated IF 50 of the pixels in a feature are above the saturation threshold Reports if the feature signal value is from the scaled up low signal image or from the high signal image The same concept as above but in case of background Boolean flag indicating if a feature is a NonUniformity Outlier or not A feature is non uniform if the pixel noise of feature exceeds a threshold established fora uniform feature The same concept as a
47. CookieCutter method Default radius The default radius is the radius of the local background for one feature This radius is known as the SELF radius and its value is the default value that you see in the Find and Measure Spots protocol step if autoestimation is turned off Feature Extraction for CytoGenomics Reference Guide Although the radius can map a circle that appears to overlap other features the Feature Extraction program does not use these pixels to calculate the local background signal Figure 42 Example of a SELF radius The value of the default radius in microns depends on the scan resolution and interspot spacing found in the TIFF and grid template or file shown in equation 1 Default Local Radius SELF 0 6 x Scan_resolution x Max Interspotspacing_x Interspotspacing_y 1 For the WholeSpot method if extraction stops at this step you may need to enter a larger radius than the protocol default radius The software autoestimates the Default Local Radius if specified in the protocol Otherwise you can enter this radius in the Feature Extraction Protocol Editor Minimum radius The minimum radius that you can enter is the FLOOR Default Radius where FLOOR rounds the calculated value of the default radius down to the next lower integer e g FLOOR 87 6 87 Maximum radius The software lets you enter a maximum radius for the local background no greater than the distance from the center of the inne
48. E MERCHANTABILITY OF THIS SOFTWARE OR ITS FITNESS FOR ANY PARTICULAR PURPOSE Stanford University School of Medicine acknowledgment Non Agilent microarray image courtesy of Dr Roger Wagner Division of Cardiovascular Medicine Stanford University School of Medicine Ultimate Grid acknowledgment This software contains material that is Copyright c 1994 1999 DUNDAS SOFTWARE LTD All Rights Reserved Feature Extraction for CytoGenomics Reference Guide LibTiff acknowledgement Part of this software is based upon LibTIFF version 3 8 0 Copyright c 1988 1997 Sam Leffler Copyright c 1991 1997 Silicon Graphics Inc Permission to use copy modify distribute and sell this software and its documentation for any purpose is hereby granted without fee provided that i the above copyright notices and this permission notice appear in all copies of the software and related documentation and ii the names of Sam Leffler and Silicon Graphics may not be used in any advertising or publicity relating to the software without the specific prior written permission of Sam Leffler and Silicon Graphics THE SOFTWARE IS PROVIDED AS IS AND WITHOUT WARRANTY OF ANY KIND EXPRESS IMPLIED OR OTHERWISE INCLUDING WITHOUT LIMITATION ANY WARRANTY OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE IN NO EVENT SHALL SAM LEFFLER OR SILICON GRAPHICS BE LIABLE FORANY SPECIAL INCIDENTAL INDIRECT OR CONSEQUENTIAL DAMAGES OF ANY KIND OR
49. Interest ROI is in terms of nominal spot spacing Find Spots SpotAnalysis_convergence_factor float Convergence factor of KMeans algorithm 74 Feature Extraction for CytoGenomics Reference Guide Table 3 List of parameters and options contained within the FULL text output file FEPARAMS table Protocol Step Find Spots Find Spots Find Spots Find Spots Find Spots Find Spots Find Spots Find Spots Find Spots Find Spots Find Spots Parameters SpotAnalysis_max_em_iter SpotAnalysis_max_reject_ratio SpotAnalysis_kmeans_rad_reject_ factor SpotAnalysis_kmeans_cen_reject_ factor SpotAnalysis_kmeans_moi_reject_ factor SpotAnalysis_isspot_factor SpotAnalysis_isweakspot_factor SpotAnalysis_BackgroundThreshold SpotAnalysis ROlType SpotAnalysis UseNominalDiameter FromGT SpotAnalysis_RejectMethod Type Options integer float float float float float float float integer integer 1 True 0 False integer 0 2 3 Description Maximum number of iterations of the Bayesian Classification Maximum fraction of pixels to be rejected while software performs spotfinding Factor that defines how much individual spot size may vary relative to the nominal spot size Factor that defines how far the actual centroid may move relative to its nominal grid position in terms of nominal radius In the protocol this parameter is called the Spot Deviation Limit Maximum a
50. LOn integer 1 True Population Outlier flagging turned on 0 False Population Outlier flagging turned off Flag Outliers OutlierFlagger_MinPopulation integer Minimum number of replicates to turn on population outlier flagging 78 Feature Extraction for CytoGenomics Reference Guide Table 3 List of parameters and options contained within the FULL text output file FEPARAMS table Protocol Step Flag Outliers Flag Outliers Flag Outliers Flag Outliers Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Feature Extraction for CytoGenomics Reference Guide Parameters OutlierFlagger_lORatio OutlierFlagger_BackgroundlORatio OutlierFlagger_Use Qtest OutlierFlagger_UsePopnOLINMAGE BGSubtractor_MultiplicativeDetrend On BGSubtractor_MultDetrendWinFilter BGSubtractor_MultDetrendIncrement BGSubtractor_MultDetrendWindow BGSubtractor_MultDetrendNeighbor hoodSize Type Options float float integer 1 True 0 False integer 1 True 0 False integer 1 True 0 False integer 0 1 2 integer integer float 0 1 Description The boundary conditions for conducting box plot analysis to isolate population outliers The boundary conditions for conducting box plot analysis to isolate population outliers for the background Enables Otest statistics when the
51. Max x0 w are optimized by using a parameterized curve fitting routine called Feature Extraction for CytoGenomics Reference Guide 55 Levenberg Marquardt and is a standard technique documented in Numerical Recipes in C on pages 683 688 f After the curve fitting is done the Low Relative Concentration is calculated as x0 2 3 w g The High relative Concentration is calculated as x0 2 2 W h All the eQC points falling between xO 2 3 w and x0 2 2 w are then fit through a line with the Slope and R Squared value reported i All of the points with a concentration below Low Concentration are used to calculate SpikeIn Detection limit For each probe the mean and standard deviation is calculated in linear BGSubSignal space Then the average plus 1 standard deviation is calculated for each probe The maximum of these is used It is converted to log10 space and reported as the SpikeIn Detection Limit Relation of curve fit calculations to statistics in table In summary the table below presents descriptions of the statistics in Figure 29 their definitions within the equation and their output in the stats table Table 2 Spike In Concentration Response Statistics for 1 color microarrays Statistic Saturation Point Low Threshold Low Threshold Error Low Signal High Signal Low Relative Concentration 56 Description Where in calculations Stats Table Output upper limit of detection max step b eQCOneColorLogHighSi
52. NA Analysts Enzymatic User Manual version 6 1 or higher ULS User Manual version 3 1 or higher The protocols come preloaded with Feature Extraction for CytoGenomics 3 0 The CytoCGH_0300_SingleCell_Nov14 protocol is for use with arrays of AMADID 067559 or 067649 which are designed for analysis of single cells For all other arrays the number of arrays per slide determines which protocol the program uses for extraction the 1x protocol for single pack format the 2x protocol for 2 pack format etc Feature Extraction for CytoGenomics Reference Guide 13 Table 1 Default settings for the preloaded CGH protocols Protocol Step Parameter Place Grid Optimize Grid Fit Grid Format Array Format For any format automatically determined or selected by you the software uses the default Placement Method listed below Parameters that apply to specific formats appear only if that format is selected Placement Method Enable Background Peak Shifting Use central part of pack for slope and skew calculation Use the correlation method to obtain origin X of subgrids The parameters and values for optimizing the grid differ depending on the format Iteratively Adjust Corners Default Setting Value v10 10 Automatically Determine Recognized formats Single Density 11k 22k 25k Double Density 44k 95k 185k 185k 10 uM 65 micron feature size also with 10 micron scans 30 micron feature size single pack and m
53. OL Features Red Red DerivedSignal Red ProcessedSig Error Red Measured Signal rMedianSignal rBGMedianSignal Red BGPixSDev rlsSaturated rlsLowPMTScaledUp rlsFeatNonUnifOL Options 1 Saturated or 0 Not saturated 1 Low 0 High g r lsFeatNonUnifOL 1 indicates Feature is a non uniformity outlier in g r Feature Extraction for CytoGenomics Reference Guide Description The propagated feature signal per channel used for computation of log ratio Standard error of propagated feature signal per channel Raw mean signal of feature in green red channel Raw median signal of feature in green red channel Median local background signal local to corresponding feature computed per channel Standard deviation of all inlier pixels per Local BG of each feature computed independently in each channel Integer indicating if a feature is saturated or not A feature Is saturated IF 50 of the pixels in a feature are above the saturation threshold For XDR features this is an integer indicating if the low PMT value was used for the calculations or the high value Integer indicating if a feature is a NonUniformity Outlier or not A feature is non uniform if the pixel noise of feature exceeds a threshold established for a uniform feature 153 Table 16 Feature results Compact contained in the MAGE ML FEATURES table Quant Features Green Features Red Options Desc
54. PixSDev rNumSatPix 1 Saturated or 0 Not saturated rlsSaturated Description Raw mean signal of feature in green red channel Raw median signal of feature in green red channel MeanSignal minus DarkOffset Standard deviation of all inlier pixels per feature This is computed independently in each channel Total Number of pixels used to compute Local BG statistics per spot i e total number of BG inlier pixels This number is computed independently in each channel Mean local background signal local to corresponding feature computed per channel Median local background signal local to corresponding feature computed per channel Standard deviation of all inlier pixels per Local BG of each feature computed independently in each channel Total number of saturated pixels per feature computed per channel Integer indicating if a feature is saturated or not A feature is saturated IF 50 of the pixels in a feature are above the saturation threshold Feature Extraction for CytoGenomics Reference Guide Table 15 Feature results Full contained in the MAGE ML FEATURES table Quant Features Green Features Red Options Description Type SQT glsLowPMTScaledUp rlsLowPMTScaledUp 1 Low For XDR features this is an integer 0 High indicating if the low PMT value was used for the calculations or the high value SQT PixCorrelation Ratio of estimated feature covariance in RedGreen space to product of
55. S section is included MAGE ML has a rich mechanism for describing protocols and protocol parameters Table 16 Feature results Compact contained in the MAGE ML FEATURES table Quant Features Green Features Red Options Description Type Ratio LogRatio base 10 log REDsignal GREENsignal per feature processed signals used to calculate log ratio If SURROGATES are turned off then 4 if DyeNormRedSig lt 0 0 amp DyeNormGreenSig gt 0 0 4 if DyeNormRedSig gt 0 0 amp DyeNormGreenSig lt 0 0 0 if DyeNormRedSig lt 0 0 amp DyeNormGreenSig lt 0 0 SOT X_IMAGE_POSITION float Found coordinates of the feature Y_IMAGE_POSITION centroid in microns Error LogRatioError If SURROGATES are turned off then 1000 if DyeNormRedSig lt 0 0 OR DyeNormGreenSig lt 0 0 IF SURROGATES are turned on then LogRatioError error of the log ratio calculated according to the error model chosen PValue PValueLogRatio Significance level of the Log Ratio computed for a feature 152 Feature Extraction for CytoGenomics Reference Guide Table 16 Feature results Compact contained in the MAGE ML FEATURES table Quant Type Derived Signal Error Measure d Signal SQT SQT Error SQT SQT SQT Features Green Green DerivedSignal Green ProcessedSig Error Green Measured Signal gMedianSignal gBGMedianSignal Green BGPixSDev glsSaturated glsLowPMTScaledU p glsFeatNonUnif
56. Signal Constant Term Multiplier Background CV 2 Red Poissonian Noise Term Multiplier Red Background Constant Term Multiplier Feature Extraction for CytoGenomics Reference Guide Default Setting Value v10 10 1 42 1 42 True False True Automatically Determine Hidden if Array Format is set to Automatically Determine True 0 04000 D 0 09000 3 17 Table 1 Default settings for the preloaded CGH protocols Protocol Step Parameter Default Setting Value v10 10 Green Poissonian Noise Term 3 Multiplier Green Background Constant Term 1 Multiplier Compute Bkgd Biasand Background Subtraction Method No Background Subtraction Error Significance for IsPosAndSignif and IsWellAboveBG Use Error Model for Significance 2 sided t test of feature vs 0 01 background max p value WellAboveMulti 13 Signal Correction Calculate Surface Fit required for True Spatial Detrend Feature Set for Surface Fit OnlyNegativeControlFeatures Perform Filtering for Surface Fit False Perform Spatial Detrending True Signal Correction Adjust Background Globally False Signal Correction Perform Multiplicative Detrending True Detrend on Replicates Only False Filter Low signal probes from Fit True Neg Ctrl Threshold Mult Detrend 3 Factor Perform Filtering for Fit Use Window Average Use polynomial data fit instead of True LOESS Polynomial Multiplicative 4 DetrendDegree Robust Neg Ctrl Stats True Choose universal error
57. Subtractor_AddErrorRed BGSubtractor_MultNcAutoEstimate BGSubtractor_MultRMSAutoEstimate BGSubtractor_MultResidualsRMSAuto Estimate BGSubtractor_AutoEstimateNCOnly Thresh Type Options integer 1 True 0 False integer 1 True 0 False float float float 0 10 float 0 10 float 0 10 float Description Auto estimation turned on Auto estimation turned off Auto estimation turned on Auto estimation turned off This additive error component in the green channel is entered in the protocol when auto estimation is turned off When auto estimation is turned on the estimated error value appears in the Stats table as AddErrorEstimateGreen This additive error component in the red channel is entered in the protocol when auto estimation is turned off When auto estimation is turned on the estimated error value appears in the Stats table as AddErrorEstimateRed Multiplier for the first term standard deviation of the inlier negative control in the additive error equation Multiplier for the second term gMultSpatialDetrendRMSFit in the additive error equation Multiplier for the third term in the additive error equation This parameter is for single density 8 pack microarrays where Feature Extraction may not be able to accurately subtract the background using the spatial detrending method This parameter provides a minimum number of features needed for the software to use the residu
58. The CV for each probe is plotted on the next page vs the average of its background corrected signal The median of these CV s is shown directly beneath the plot 4660 9320 13980 18640 23290 Ave _BGSubsignal CY for Red SCY for Green Median CV 10 21 Red 10 57 Green Figure 22 QC Report Agilent Spikelns CV of Average BGSub Signal 46 Feature Extraction for CytoGenomics Reference Guide Reproducibility plot for 1 color gene expression spike in probes This graph plots CV vs the log_gMedianProcessedSignal for the 1 color gene expression microarray experiment The region where the CV flattens out and is not tightly correlated with signal is the range where noise is proportional to signal This is generally the range used to calculate the median CV Agilent SpikeIns CV of Avg Processed Sign Log _oMecianProcessedSignal CY for Green Median CV 6 17 Figure 23 1 color QC Report Agilent Spikelns CV of Avg Processed Signal Plot Feature Extraction for CytoGenomics Reference Guide 4 48 Reproducibility plot for miRNA non control probes This graph plots CV vs the log_gMedianProcessedSignal for the 1 color miRNA microarray experiment The region where the CV flattens out and is not tightly correlated with signal is the range where noise is proportional to signal This is generally the range used to calculate the median CV ility CV for Replicated Probes plot Log_oMedianProces
59. The number of pixels that are removed as outliers at the high end and low end of the intensity distribution are shown in 4 columns of the FEATURES table NumPixOLLo and NumPixOLHi for both red and green channels Step 8 Calculate the mean signal of the local background BGMeanSignal The intensities of local background inlier pixels are averaged to give the local background mean signal The BGNumPix column in the result file lists the number of inlier pixels in the local background radius that remain after rejection of outlier pixels BGMeanSignal X 5 i l where n is the of inlier pixels in the local background i e BGNumPix and X is the pixel intensity in the local background Step 9 Determine if the feature is saturated IsSaturated Feature is saturated if 50 of inlier pixels have intensity values above the saturation threshold Feature Extraction for CytoGenomics Reference Guide 183 Flag Outliers oy is the measured variance ot inlier pixels in the feature or background e g PixSDev2 or BGPixSDev2 oF is the estimated variance using known noise characteristics of the Agilent Microarray Gene Expression system For more information on contidence interval check Numerical Recipes in C Chapter 15 page 692 Net signal is the mean signal i e MeanSignal or BGMeanSignal respectively minus the MinSigArray which is minimum feature signal or minimum local background signal on the microarray
60. ackground correction for the background This is implemented as an incomplete Beta Function approximation X Y aeaa A a 2 2 i acd Ge df np n where X p is the mean signal MeanSignal of the feature and X g is the background correction used for subtraction BGUsed see Table 20 on page 190 where Mp and N are the number of inlier pixels in the feature or background local respectively e g NumPix or BGNumPix where a and o are variances of inlier pixels for feature and background respectively e g PixSDev or BGSDUsed n 1 2 5 l X Xp 17 X is pixel intensity F i 0 n 1 2 l r 53 L X X5 18 B i 0 Feature Extraction for CytoGenomics Reference Guide 205 206 where df is the degrees of freedom df pt Np 2 After the p value is calculated from the 2 sided t test using incomplete Beta Function it is compared to the user defined max p value If the calculated p value from the Beta Function is less than the user defined max p value then the feature signal is considered to be significantly different from the background signal If p value calculated lt P VAlUEe Max and if MeanSignal gt BGUsed then feature gets a Boolean flag of 1 under the IsPosAndSignif column in Feature Extraction result file Significance based on additive error The Error model significance also uses a Gaussian probability distribution for the calculation and tests to see if a signal is
61. action for CytoGenomics Reference Guide Plot of LogRatio vs Log ProcessedSignal LogProcessedSignal in the plot is Log rProcessedSignal x gProcessedSignal 2 This plot shows the log ratios of non control inliers vs the log of their red and green processed signals The color coding signifies the degree to which features are significantly differentially expressed those that are up regulated red those that are down regulated green and those that cannot confidently be said to show gene expression light yellow For the CGH QC Report these are referred to as Positive Negative log ratios base 2 The threshold that is used to determine significance is set in the protocol QCMetrics_differentialExpressionPValue Features that were used for normalization are indicated in blue Significance takes precedence over normalization for the color coding that is features that are both significantly differentially expressed and used for normalization will be color coded either red or green SNP probes are not included LogRatio Versus Log Processed Signal LogProcessedSignal significantly down regulated significantly up regulated Used to normalize Mot differentially expressed Figure 16 QC Report Plot of Up and Down Regulated Features Feature Extraction for CytoGenomics Reference Guide 39 Spatial Distribution of Median Signals for each Row and Column Higher frequency noise is shown in these plots so
62. action of features that are not found along any edge of the microarray Root mean square RMS of the fitted data points obtained from the second degree polynomial equation in Multiplicative Detrending This gives an idea of the curvature of the surface fit to the hybridization dome in the Agilent Hybridization chambers Feature Extraction for CytoGenomics Reference Guide 105 Table 7 Stats results contained in the text output file STATS table continued Stats Green Channel gMultDetrendSurfaceAverage DerivativeOfLogRatioSD eQCLowSigNamel eQCLowSigName2 eQCOneColorLogLowSignal eQCOneColorLogLowSignal Error eQCOneColorLogHighSignal eQCOneColorLinFitLogLowConc eQCOneColorLinFitLogLow Signal Stats Red Channel rMultDetrendSurfaceAverage Type float float text text float float float float float Description The average of the surface calculated by multiplicative detrending This average is used to normalize the surface It is a straight average over all the points in the surface Measures the standard deviation of the probe to probe difference of the log ratios This is a metric used in CGH experiments where differences in the log ratios are small on average A smaller standard deviation here indicates less noise in the biological signals The probe name of the eQC probe spiked in at the lowest concentration The probe name of the eQC probe spiked i
63. al Bkgnd Adjust ON Adjust GBA OFF No BGUsed BGMeanSignal SpatialDetrend BGAdjust SpatialDetrendSurface background SurfaceValue Value SDSV BGAdjust subtract t l BGSDUsed BGPixSDev BGPixSDev BGPixSDev BGPixSDev BGSubSignal MeanSignal MeanSignal MeanSignal MeanSignal BGUsed BGUsed BGUsed Local BGUsed BGMeanSignal BGMeanSignal BGMeanSignal BGMeanSignal SDSV Background SDSV BGAdjust BGAdjust BGSDUsed BGPixSDev BGPixSDev BGPixSDev BGPixSDev 190 Feature Extraction for CytoGenomics Reference Guide Table 20 Values for BGSubSignal BGUsed and BGSDUsed for different methods and settings continued Background Background Spatial Detrend SpDe ON SpDe OFF Spatial Detrend ON Subtraction Subtraction SpDe OFF Method Variable Global Bkgnd GBA OFF GBA ON Global Bkgnd Adjust ON Adjust GBA OFF BGSubSignal MeanSignali MeanSignal MeanSignal MeanSignal BGUsed BGUsed BGUsed BGUsed Global BGUsed GlobalBGInlierAve GBGIA SDSV GBGIA GBGIA SDSV BGAdjust Background GBGIA BGAdjust method BGSDUsed GlobalBGInlierSDev GBGISD GBGISD GBGISD GBGISD BGSubSignal MeanSignali MeanSignal MeanSignal MeanSignal BGUsed BGUsed BGUsed BGUsed For both the red and green channels 2 color CGH and non Agilent microarrays t With No background subtraction as the setting BGMeanSignal is the value for BGUsed only for the t test but no BGUsed is subtracted from the MeanSignal to produce BGSubSignal t If the me
64. al or the RMS to estimate the additive error It comes up only if using low density 8 pack microarrays 84 Feature Extraction for CytoGenomics Reference Guide Table 3 List of parameters and options contained within the FULL text output file FEPARAMS table Protocol Step Compute Bkgd Bias and Error Compute Bkgd Bias and Error Correct Dye Biases Correct Dye Biases Correct Dye Biases Correct Dye Biases Correct Dye Biases Correct Dye Biases Feature Extraction for CytoGenomics Reference Guide Parameters BGSubtractor_UseSurrogates BGSubtractor_Version DyeNorm_Version DyeNorm_UseDyeNormList DyeNorm_SelectMethod DyeNorm_ArePosNegCtrlsOK DyeNorm_SignalCharacteristics DyeNorm_CorrMethod Type Options integer 1 True 0 False text text integer 0 1 2 integer am Aa A integer 1 True 0 False integer 1 2 3 integer Description Flag indicating the use of surrogates Use of surrogates turned on Use of surrogates turned off Version of BGSubtractor algorithm Version of DyeNorm algorithm Automatically determine True False Method for selecting features used for measurement of dye bias Use All Probes Use List of Normalization Genes Use Rank Consistent Probes Use Rank Consistent List of Normalization Genes Use positive and negative controls for dye normalization Do not use these controls Only positive and significant signals A
65. alculating the average SD and CV of the processed signal of each replicated probe For non control replicated probes there must be at least 10 CVs from which to calculate a median otherwise 1 is reported The MedPrentCVProcSignal and the MedPrentCVBGSubSignal show if Multiplicative Detrending is having a positive effect on the data If multiplicative detrending is helping the MedPrentCVProcSignal should be smaller than the MedPrentCVBGSubSignal This is the same as MedPrentCVProcSignal except that it is performed using the eQC Spikeln Replicates rather than the nonControl Replicates There must be at least 3 CVs from which to calculate a median Applies to feature specifies the variance due to the Poisson distributed noise automatically calculated when OLAutoCompute is turned on Applies to feature specifies variance due to background noise of the scanner slide glass and other signal independent sources automatically calculated when OLAutoCompute is turned on Applies to background specifies the variance due to the Poisson distributed noise automatically calculated when OLAutoCompute is turned on Feature Extraction for CytoGenomics Reference Guide Table 7 Stats results contained in the text output file STATS table continued Stats Green Channel gOutlierFlagger_Auto_BgndC Term OutlierFlagger_FeatChiSg OutlierFlagger_BgndChiSq gXDRLowPMTSlope gXDRLowPM Intercept GriddingStatus NumGeneN
66. alization features The amount of dye bias is determined from the curve at each feature s intensity Each feature gets a different LOWESS dye normalization factor per channel The LOWESS method corrects the log ratio data so that its central tendency after dye normalization lies along zero for all intensity ranges assuming an equal number of up and down regulated features in any given signal range The Feature Extraction for CytoGenomics Reference Guide Note that the Linear amp LOWESS dye normalization factor is not reported in the Feature Extraction output file Therefore the only way to know the Linear amp Lowess dye norm factor is to calculate it using the equation below Linear amp LOWESSDyeNorm Factor LOWESS DyeNormF actor is derived for each channel by the procedure described on the next page a A linear regression curve is fit to the data in a plot of M vs A where M y axis Log R G and A x axis 1 2 x Log R G R and G represent the red and green background subtracted signals This LOWESS curve fit through the central tendency of the M vs A plot is defined as Mfit and is a function of A b The dye normalization step transforms the data so that the central tendency of Mfit at every A is shifted to be equal to zero c After the correction factor is determined for any feature it is split evenly over the red and green channels The new signals after correction R and G are obtained by transformin
67. alized Quantitation Type Feature Extraction for CytoGenomics Reference Guide Description Boolean flag established via a 2 sided t test indicates if the mean signal of a feature is greater than the corresponding background selected by user and if this difference is significant To display variables used in the t test see Table 20 on page 190 P value from t test of significance between g r Mean signal and g r background Boolean flag indicating if a feature is WellAbove Background or not Feature passes g r IsPosAndSignif and additionally the g r BGSubSignal is greater than 2 6 g r BGSDUsed Set to true for a given feature if it is part of the filtered set used to detrend the background This feature is considered part of the locally weighted lowest x of features as defined by the DetrendLowPassPercentage Value of the smoothed surface calculated by the Spatial detrend algorithm A boolean used to flag features used for computation of global BG offset Background used to subtract from the MeanSignal variable also used in t test To display the values used to calculate this variable using different background signals and settings of spatial detrend and global background adjust see Table 20 on page 190 151 Table for Compact Output Package This table contains only those columns required by Resolver GenesSpring CGH Analytics and Chip Analytics In the Compact version of the MAGE ML file the entire FEPARAM
68. alueLogRatio 1 g r ProcessedSignal g r SurrogateUsed g r DyeNormFactors Calculate Metrics Although the QC metrics are calculated in this step only the gridding tests are discussed in this section Step 28 Perform a series of gridding tests to make sure that grid placement has been successful These tests are performed to yield warnings on the Summary Reports about unsuccessful gridding They also produce the assessment shown in the QC Report of whether the grid needs to be evaluated or not In Feature Extraction new tests have been added and thresholds tuned to decrease the number of false negatives Feature Extraction for CytoGenomics Reference Guide 217 218 Test 1 Test 2 Test 3 Test 4 Test 5 Summary Report shows no problems when there are and false positives Summary Report shows a problem when there isn t The parameters for these tests do not appear in the protocols but they do appear in the FEParams output Below is a question asked by each test the metric used to answer the question stat name that appears in the result text file as the Statistics table and the threshold to assess gridding success or failure If a grid fails any one of these tests a warning or warnings appear in the reports How many features are not found along the edge of the microarray Stat name MaxSpotNotFoundEdges Threshold_Max 0 72 How many local background regions are flagged as non unifo
69. are Documentation Safety Notices CAUTION A CAUTION notice denotes a haz ard It calls attention to an operat ing procedure practice or the like that if not correctly performed or adhered to could result in damage to the product or loss of important data Do not proceed beyond a CAUTION notice until the indicated conditions are fully understood and met A WARNING notice denotes a hazard It calls attention to an operating procedure practice or the like that if not correctly per formed or adhered to could result In personal injury or death Do not proceed beyond a WARNING notice until the indicated condi tions are fully understood and met Feature Extraction for CytoGenomics Reference Guide In This Guide This Reference Guide contains tables that list default parameter values and results for Agilent Feature Extraction for CytoGenomics analyses and explanations of how Feature Extraction for CytoGenomics uses its algorithms to calculate results 1 Protocol Default Settings This chapter includes tables that list the default parameter values found in the protocols shipped with the software 2 QC Report Results Learn how to read and interpret the QC Reports 3 Text File Parameters and Results This chapter contains a listing of parameters and results within the text file produced after Feature Extraction 4 XML MAGE ML Results Refer to this chapter to find the results contained in the MAGE ML fil
70. are off center in one or more corners you may have to run the extraction again with a new grid Grid Normal Figure 5 QC Report Spot Finding for Four Corners Feature Extraction for CytoGenomics Reference Guide Outlier Stats If the QC Report shows a greater than expected number of non uniform or population outliers you may want to check your hybridization wash step Also check the visual results shp file to see if the spot centroids are off center If the grid was not placed correctly a new grid is required Local Background Red Green Red Green Feature Non Uniform 4 8 9 0 Population 98 Za 48 0 Figure 6 QC Report Outlier Stats For 1 color reports the number of outliers is reported for the green channel only Spatial Distribution of All Outliers The QC report shows two plots of all the outliers both population and nonuniformity outliers whose positions are distributed across the microarray One plot is for the green channel and the other for the red channel SNP probes are included To distinguish the background population and nonuniform outliers from one another look at the color coding at the bottom of the two plots For the 1 color report only the green plot is shown Feature Extraction for CytoGenomics Reference Guide 29 30 Spatial Distribution of All Outliers on the Array 105 rows x 215 columns FeatureNonUnif Red or Green 11 0 05 GeneNonUnif Red or Green 5 0
71. at result file 143 MAGE ML result file feature results 146 152 protocol parameters 145 scan protocol parameters 144 Feature Extraction for CytoGenomics Reference Guide multiplicative detrend algorithm 1 color 208 N nonuniformity outliers estimated feature or bkgd variance 184 measured feature or bkgd variance 186 0 outliers criteria for rejecting 182 interquartile range method 182 standard deviation method 182 output files control types 157 how used by databases 142 integrating with Resolver 156 text 69 p parameter options 71 place grid find nominal spot positions 174 public accession numbers 139 225 Index Q QC Report foreground surface fit 35 local background inliers 35 microarray uniformity 44 net signal statistics 29 outlier number and distribution 29 plot of background corrected signals 33 plot of LogRatio vs Average Log Signal 39 reproducibility plot spike ins 46 reproducibility statistics non control probes 42 results in FEPARAMS and STATS table 59 sensitivity 45 spike in log ratio statistics 46 spot finding four corners 28 up and down regulated features 38 QC Report 1 color only Histogram of Signals Plot 34 Multiplicative Surface Fit 37 Spatial Distribution of Median Signals 40 QC Report Types 1 color gene expression 22 results features 114 integrating with Resolver 156 QC Report parameters and stats 59 Statistical 98 text file 6
72. atPix Features Red rNumPix rMeanSignal rMedianSignal rPixSDev rPixNormlOR rBGNumPix rBGMeanSignal rBGMedianSignal rBGPixSDev rBGPixNormlQR rNumSatPix Types Options Description integer Total number of pixels used to compute feature statistics i e total number of inlier pixels per spot same in both channels float Raw mean signal of feature from inlier pixels in green and or red channel float Raw median signal of feature from inlier pixels in green and or red channel float Standard deviation of all inlier pixels per feature this is computed independently in each channel float The normalized Inter quartile range of all of the inlier pixels per feature The range is computed independently in each channel integer Total number of pixels used to compute local BG statistics per spot i e total number of BG inlier pixels same in both channels float Mean local background signal local to corresponding feature computed per channel inlier pixels float Median local background signal local to corresponding feature computed per channel inlier pixels float Standard deviation of all inlier pixels per local BG of each feature computed independently in each channel float The normalized Inter quartile range of all of the inlier pixels per local BG of each feature The range is computed independently in each channel integer Total number of saturated pixels per feature computed p
73. ations and diagram Assumptions for default value of 1 42 The following assumptions lead to the default value of 1 42 for this parameter e Normal distribution for pixel intensity where y axis corresponds to pixel frequency and x axis corresponds to pixel intensity e A 99 confidence interval that the pixels of interest are contained within the boundaries for rejection Feature Extraction for CytoGenomics Reference Guide 181 The nterquartile Range IQR is the range of points under a Gaussian distribution contained between the 25th percentile mark 25 of the points are contained under the curve from the zero point to the 25th percentile mark and the 75th percentile mark The 50th percentile mark is coincident with the median of the curve The boundary for rejection is the point on the x axis beyond which all pixels will be rejected D is the distance between the mean of the curve and the boundary for rejection 182 Calculations of default value The following calculations are based on the above assumptions e Ifa pixel is located within the 99 confidence interval it is 2 6 standard deviations SD away from the mean Or D 2 6 SD and D Mult _ factorxIOR k e From the Z table for cumulative normal frequency distribution the Zp p 75 0 675 K 0 675x SD IQR 2 e If you combine the four equations above and solve for the Mult_factor the Mult_factor 1 42 e If you would rather use a 95 confidenc
74. ays produce plots missing the top asymptote especially if extended dynamic range is used See the plot below 52 This plot shows the dose response curve of the spike ins from the detection limit to the saturation point At high signal levels the error bars are small since the scanner reaches saturation at this point Both the signals and standard deviations are underestimated because the saturated data is not excluded from the calculation At low signal levels the error bars are visible because the signal is dropping into the background noise The signal level at the top of the error bars of the features with lowest signal provides a rough estimate of the lower limit of detection Signals at this level can be slightly overestimated and the error slightly underestimated because the signals below zero are excluded from the calculation The most reliable Feature Extraction data is found in the signal range where the signal increases linearly with the concentration of the target Agilent SpikeIns Log Signal vs Log Relative concentration Plot 5 38 453 4 33 383 EEE 2 33 233 1 83 1 33 0 83 0 33 t cu Gi wd T o i ie 1i i pam LL C 1 o di ta Gi m d O17 020 060 150 2500 380 4 50 560 6 60 Log Concentration Frocessed Sig Vs Concentration Figure 28 1 color QC Report Agilent Spikelns Log Signal vs Log Relative concentration Plot Feature Extraction f
75. ble9 Feature results contained in the COMPACT output text file COMPACT FEATURES table continued Features Green LogRatio base 10 LogRatioError PValueLogRatio gProcessedSignal Features Red Types Options float 4 4 0 float 1000 float rProcessedSignal float Feature Extraction for CytoGenomics Reference Guide Description per feature log of rProcessedSignal gProcessedSignal If SURROGATES are turned off then if DyeNormRedSig lt 0 0 amp DyeNormGreenSig gt 0 0 if DyeNormRedSig gt 0 0 amp DyeNormGreenSig lt 0 0 if DyeNormRedSig lt 0 0 amp DyeNormGreenSig lt 0 0 If SURROGATES are turned off then if DyeNormRedSig lt 0 0 OR DyeNormGreenSig lt 0 0 IF SURROGATES are turned on then LogRatioError error of the log ratio calculated according to the error model chosen Significance level of the Log Ratio computed for a feature The signal left after all the Feature Extraction processing steps have been completed In the case of one color ProcesssedSignal contains the Multiplicatively Detrended BackgroundSubtracted Signal if the detrending is selected and helps If the detrending does not help this column will contain the BackgroundSubtractedSignal 125 Table 9 Feature results contained in the COMPACT output text file COMPACT FEATURES table continued Features Green gProcessedSigError gMedianSignal gBGMedianSignal gBGPixSDev glsSa
76. bove but for background outlier in g r 132 Feature Extraction for CytoGenomics Reference Guide Table 10 Feature results contained in the OC output text file QC FEATURES table Features Green glsFeatPopnOL glsBGPopnOL IsManualFlag gBGSubSignal glsPosAndSignif glsWellAboveBG Features Red rlsFeatPopnOL rlsBGPopnOL rBGSubSignal rlsPosAndSignif rlsWellAboveBG Types boolean boolean boolean float Boolean Boolean Options g r lsFeatPopnOL 1 indicates Feature is a population outlier in g r g r IsBGPopnOL 1 indicates local background is a population outlier in g r g r BGSubSignal g r MeanSignal g r BGUsed g r isPosAndSignif indicates Feature is positive and significant above background Feature Extraction for CytoGenomics Reference Guide Description Boolean flag indicating if a feature is a Population Outlier or not Probes with replicate features on a microarray are examined using population statistics A feature is a population outlier if its signal is less than a lower threshold or exceeds an upper threshold determined using a multiplier 1 42 times the interquartile range i e IQR of the population The same concept as above but for background Flags features for downstream filtering in third party gene expression software Background subtracted signal To display the values used to calculate this variable using differen
77. ction program may or may not have performed correctly But you should check the data in this case to confirm that the XDR combination is satisfactory This message is more likely to appear as the low intensity PMT gain setting gets closer 1 This is because the percentage error in the PMT gain setting increases as the setting moves away from 100 Feature Extraction for CytoGenomics Reference Guide 173 How each algorithm calculates a result 174 Place Grid Step 1 Place a grid to find the nominal spot positions After the Feature Extraction program automatically determines the format of the grid it initiates the next steps The algorithm reduces the two dimensional image data of the microarray to two one dimensional data sets that are further processed to determine the layout of the grid on the microarray Projection of the two dimensional microarray is performed to produce two one dimensional data sets projected signals From the one dimensional data sets peaks of the projected signals are filtered to determine which peaks to retain for further processing based on predetermined peak height and peak width thresholds Nominal spacing between the features may be estimated based on a Statistical determination of a most frequent distance between centers of retained peaks that are adjacent to one another Coordinates for the features on the microarray relative to the X and Y axes are generated based on the selected peaks and p
78. d For global background methods the standard deviation of the background is at the replicate background population level of the microarray If Error model significance is used to calculate IsPosAndSignif then SurrogateUsed AddError LinearDyeNormFactor 20 where AddError is the additive error from the Error Model calculation If Multiplicative Detrending is used the SurrogateUsed is scaled by the MultDetrendSignal for each feature If a p value other than default 0 01 is chosen in the protocol then the SurrogateUsed is adjusted appropriately Step 20 Perform multiplicative detrending Multiplicative detrending is an algorithm designed to compensate for slight linear variations in intensities that can occur if the processing is not homogeneous across the slide This non homogeneous processing results in different chemical reaction times for example between the sides and the center and produces a dome effect With 2 color microarrays these dome effects are the same in each channel and for the most part cancel out during the calculations Agilent has found multiplicative detrending to still be useful however for all the microarrays This algorithm is designed to correct the data by fitting a smoothed surface via a second degree polynomial fit to the Feature Extraction for CytoGenomics Reference Guide higher signals on the microarray after outliers are rejected This is shown in the illustration below Fit
79. d Bias and Error Section the DNF is 1 and the Variance of the NegCtrls are not scaled for the DNF either This scaling is done to the AdditiveError after DyeNorm is completed 2 as ONesCirl Variance of the inlier negative control where inlier negative control implies the negative controls for the corresponding channel after rejections of saturated population and non uniform outliers where SpatialDetrendRMSFit RMS of the points defining the surface fit for that channel For more details on this term see Table 21 on page 197 For Agilent 8 x format oligo microarrays the auto estimation algorithm uses only the variance of the inlier negative controls You can set m1 or m2 in equation 22 equal to zero in the protocol settings Feature Extraction for CytoGenomics Reference Guide 203 MultNcAutoEstimate MultRMSAutoEstimate MultResidualRMSAutoEstimate 204 Multiplier for the first term in the additive error equation standard deviation of the inlier negative control The value changes depending on the protocol used GE1 GE2 and miRNA 0 CGH and ChIP 1 non Agilent 1 Multiplier for the second term in the additive error equation g r SpatialDetrendRMSFit This term is proportional to the amount of sequence variability in the foreground On gene expression arrays Agilent uses this term because there is a single sequence for all negative controls so an estimation of any sequence dependent foreground noise usi
80. d IQR and number of inlier pixels XDR extraction This is the only step that is run twice on an XDR extraction The spot placement and spot measurements are found separately for the high and low intensity scans Then the XDR algorithm decides on a feature by feature basis which scan the data should come from more on this below For features that are very bright in the high intensity scan the XDR algorithm uses the data from the low intensity scan This choice is made independently for each color channel For each feature that uses data from the low intensity scan the following columns get replaced determined separately for red and green channels NumPixOLHi NumPixOLLo NumPix MeanSignal MedianSignal PixSDev PixNormIQR NumSatPix IsSaturated NetSignal These columns include the raw data from the spotfinding and measurement steps signal levels pixel noise levels number of pixels if the pixels and feature are saturated Once the substitutions have been made to some features in each color channel the extraction proceeds as if there were only a single combined set of features Flag Outliers Next the Flag Outliers algorithm flags anomalous features and local backgrounds as non uniformity outliers and or population outliers Population outlier flagging is based on population statistics of replicate features on the microarray Which of two statistical tests is used to identify population outliers depends on the number of rep
81. e See Ch 4 for definition 30000 Ignore See Ch 4 for definition ProbeName text An Agilent assigned identifier for the probe synthesized on the microarray SystematicName text This is an identifier for the target sequence that the probe was designed to hybridize with Where possible a public database identifier is used e g TAIR locus identifier for Arabidopsis Systematic name is reported ONLY if Gene name and Systematic name are different Feature Extraction for CytoGenomics Reference Guide 135 Table 11 Feature results contained in the MINIMAL output text file MINIMAL FEATURES table Features Green Features Red LogRatio base 10 LogRatioError PValueLogRatio gProcessedSignal rProcessedSignal 136 Types float float float float Options 1000 Description per feature log of rProcessedSignal gProcessedSignal If SURROGATES are turned off then if DyeNormRedSig lt 0 0 amp DyeNormGreenSig gt 0 0 if DyeNormRedSig gt 0 0 amp DyeNormGreenSig lt 0 0 if DyeNormRedSig lt 0 0 amp DyeNormGreenSig lt 0 0 If SURROGATES are turned off then if DyeNormRedSig lt 0 0 OR DyeNormGreenSig lt 0 0 IF SURROGATES are turned on then LogRatioError error of the log ratio calculated according to the error model chosen Significance level of the LogRatio computed for a feature The signal left after all the Feature Extraction processing steps have been co
82. e QC output text file QC FEATURES table Features Green FeatureNum Row Col Sub lypeMask Controllype ProbeName SystematicName Description PositionX PositionY Features Red Types integer integer integer integer integer text text text float Options 15000 20000 30000 Description Feature number Feature location row Feature location column Numeric code defining the subtype of any control feature Feature control type See XML Control Type output on page 156 for definitions Control type none Positive control Negative control SNP Not probe See Ch 4 for definition Ignore See Ch 4 for definition An Agilent assigned identifier for the probe synthesized on the microarray This is an identifier for the target sequence that the probe was designed to hybridize with Where possible a public database identifier is used e g TAIR locus identifier for Arabidopsis Systematic name is reported ONLY if Gene name and Systematic name are different Description of gene Found coordinates of the feature centroid in microns Feature Extraction for CytoGenomics Reference Guide 129 Table 10 Feature results contained in the QC output text file QC FEATURES table Features Green Features Red LogRatio base 10 LogRatioError PValueLogRatio gProcessedSignal rProcessedSignal 130 Types float float float float Options
83. e eXtended Dynamic Range XDR to cover the full dynamic intensity range of your microarray features and hence see the most useful biology To do this you set the scanner to scan twice once at a high PMT setting the high intensity scan followed immediately by a low PMT setting the low intensity scan This functionality is enabled using Agilent Scan Control Software version 7 0 The two scans are labeled in their tiff headers as paired scans of the same microarray XDR Feature Extraction process The Feature Extraction program v9 1 and later uses this information to know to extract the low and high PMT images as a pair In this XDR extraction type the Feature Extraction program processes the two scans together and produces a single set of outputs that contain data from both scans Some of the features contain data from the high intensity scan and some from the low intensity scan You can determine this by viewing the column r glsLowPMTScaledUp for each color channel For signals that are very bright or saturated in the high intensity scan e g a scan at 100 PMT gain the XDR algorithm substitutes the data from the low intensity scan e g 10 PMT gain after scaling the intensity appropriately Feature Extraction for CytoGenomics Reference Guide Feature Extraction for CytoGenomics Reference Guide To extract these arrays the Feature Extraction program uses a somewhat different flow of the image processing and data anal
84. e expected versus observed average log ratio for each spike in probe For 2 color QC report Intercept of the linear regression fit of the plot of the expected versus observed average log ratio for each spike in probe 104 Feature Extraction for CytoGenomics Reference Guide Table 7 Stats results contained in the text output file STATS table continued Stats Green Channel Stats Red Channel eQCObsVsExpCorr NumlsNorm ROI Width ROI Height CentroidDiffX CentroidDiffY NumFoundFeat MaxNonUnifEdges MaxSpotNotFoundEdges gMultDetrendRMS Fit rMultDetrendRMS Fit Type float integer float float float integer float float float Description For 2 color OC report The R2 value of the linear regression fit of the plot of the expected versus observed average log ratio for each spike in probe Number of features used for normalization The width or height in pixels of the region of interest ROI about a nominal spot location The spotfinder determines the found centroid and spot size of the spot within the ROI The average absolute of difference between nominal centroids and corresponding found centroids in X direction The average absolute of difference between nominal centroids and corresponding found centroids in Y direction The number of features that are flagged as found Maximum fraction of features that are non uniform along any edge of the microarray Maximum fr
85. e interval IQR Mult_factor 0 952 The reason for this is assuming normal distribution and infinite degrees of freedom D 1 96 SD 0 95185xJOR k Therefore K I0R 2 1 42 10F A 50 ile 25 Wile Patol Boundary for rejection Boundary for rejection IO Figure 45 Important points on Gaussian curve of pixels vs intensity Step 7 Calculate the mean signal of the feature MeanSignal The intensities of inlier pixels of a feature are averaged to give mean signal of the feature before background subtraction The NumPix column in the result file lists the number of inlier pixels in the cookie that remain after rejection of outlier pixels Feature Extraction for CytoGenomics Reference Guide If the method in the protocol for calculating the spot value from pixel statistics has been chosen to be Median Normalized InterQuartile Range instead of Mean Standard Deviation the program makes these substitutions for the spot value and background subtraction calculations MedianSignal for MeanSignal BGMedianSignal for BGMean Signal PixNorm IQR for PixSDev GPixNorml0R for BGPixSDev NormlOR 0 7413 x IQR The program does not make these substitutions for the Feature NonUniformity Outlier algorithm See the previous page for the definition of the Interquartile Range IQR MeanSignal bs gt X 4 i l where n is the of inlier pixels i e NumPix and X is pixel intensity in the feature
86. e name Date the grid template or grid file was created Number of subgrid columns Number of subgrid columns Number of spots per row of each subgrid Number of spots per column of each subgrid Space between rows on the grid Space between column on the grid In a dense pack array the offset in the X direction Feature Extraction for CytoGenomics Reference Guide Table 5 List of parameters and options contained within the QC text output file FEPARAMS table Protocol Step Parameters Type Options Description Grid_OffsetY float In a dense pack array the offset in the Y direction Grid_NomSpotWidth float Nominal width in microns of a spot from grid Grid_NomSpotHeight float Nominal height in microns of a spot from grid Grid_GenomicBuild text The build of the genome used to create the annotation if available If the genome build is not available not all designs have this information then it is not put out All recent and all future designs have it FeatureExtractor Barcode text Barcode of the Agilent microarray read from the scan image FeatureExtractor_ Sample text Names of hybridized samples red green FeatureExtractor_ ScanFileName text Name of the scan file used for Feature Extraction FeatureExtractor_ArrayName text Microarray filename FeatureExtractor ScanFileGUID text GUID of the scan file FeatureExtractor_DesignFileName text Design or grid file used for Feature Extraction FeatureExtractor_Extractionlime text
87. eak spacing The grid is then adjusted for rotation and skew The background peak shift flag helps to improve the gridding Ideally all background pixels should have a gray value of zero In practice these values are nonzero When this flag is set to true the algorithm determines the background pixels pixel value from the histogram of the image All pixels having a non zero value background window are set to zero thus reducing the contribution of background pixels in the two one dimensional projected signals This shift in the peak of the background signal leads to better determination of peaks Feature Extraction for CytoGenomics Reference Guide The following figures illustrate the result of applying Background Peak Shifting Figure 37 is a histogram of a typical 30 micron feature array before Background Peak Shifting Figure 38 depicts the same array after applying Background Peak Shifting Note that this operation is done internally in the grid placement algorithm The actual image data remains unchanged Some variations in the results are expected with and without use of this flag as the grid positions obtained differ 4000000 4 3000000 2000000 Frequency Red 1000000 Frequency Green 0 o 5000 10000 15000 20000 25000 30000 35000 Figure 37 Histogram of a 30 micron feature array image The X axis cor responds to the pixel value and the Y axis to the frequency of occurrence 4000000
88. earlier When the flag is set to True the software performs one extra step of correlation following the projection data analysis to get the origin This option is of use particularly in cases where pack edges have dim spots and are failing to grid 176 Feature Extraction for CytoGenomics Reference Guide Optimize Grid Fit Step 2 Iteratively adjust grid by examining the corner spots This algorithm improves the grid fit by leveraging from the Spot Finder algorithm Looking only at the specified square area of features at each corner of the microarray it performs the iteratively adjust corners method up to the maximum number of iterations specified in the protocol It adjusts the grid only if the following criteria are met e The absolute average difference between the grid position and the spot position is within the specified Adjustment Threshold e The number of features considered found by the spot finder algorithm is within the specified Found Spot Threshold Find Spots Step 3 Locate the spot centroids The calculation is based on an iterative Bayesian probability based pixel classification A binary feature mask is created that classifies the pixels in a region of interest around each grid position into feature pixels or background pixels The approximate radius of each feature mask is considered as the corresponding spot radius and the center of mass of the feature mask is considered as the actual spot centroid In the
89. eatureExtractor_ComputerName FeatureExtractor_Version FeatureExtractor_IsXDRExtraction Type Options float float float text text text text text text text text text text text integer 1 True 0 False Description In a dense pack array the offset in the Y direction Nominal width in microns of a spot from grid Nominal height in microns of a spot from grid The build of the genome used to create the annotation if available If the genome build is not available not all designs have this information then it is not put out All recent and all future designs have it Barcode of the Agilent microarray read from the scan image Names of hybridized samples red green Name of the scan file used for Feature Extraction Microarray filename GUID of the scan file Design or grid file used for Feature Extraction Time stamp at the beginning of Feature Extraction Windows Log In Name of the User who ran Feature Extraction Computer name on which Feature Extraction was run Version of Feature Extractor Says if result is from an XDR extraction Feature Extraction for CytoGenomics Reference Guide Table 4 List of parameters and options contained within the COMPACT text output file FEPARAMS table Protocol Step Parameters Type Options Description FeatureExtractor_ColorMode integer A flag to indicate output color 0 One color green only 1 2 color FeatureExtractor QCReportlype in
90. ed Probes 42 Microarray Uniformity 2 color only 44 Sensitivity 45 Reproducibility Plots 46 Spike in Signal Statistics 49 Spike in Linearity Check for 2 color Gene Expression 51 Spike in Linearity Check for 1 color Gene Expression 52 QC Report Results in the FEPARAMS and Stats Tables 59 QC Metric Set Results 60 CytoCGH_ OQCMT 1x_Marl4 61 CytoCGH OCMT 2x Mar14 62 CytoCGH OCMT 4x Marl4 63 CytoCGH OCMT 8x _Marl4 64 CytoCGH OCMT SingleCell Novi4 65 Metric Evaluation Logic 66 Text File Parameters and Results Parameters options FEPARAMS 71 FULL FEPARAMS Table 71 COMPACT FEPARAMS Table 89 QC FEPARAMS Table 92 MINIMAL FEPARAMS Table 95 Statistical results STATS 98 STATS Table ALL text output types 98 Feature results FEATURES 114 FULL Features Table 114 COMPACT Features Table 124 Feature Extraction for CytoGenomics Reference Guide OC Features Table 129 MINIMAL Features Table 135 Other text result file annotations 139 4 MAGE ML XML File Results How Agilent output file formats are used by databases 142 MAGE ML results 143 Differences between MAGE ML and text result files 143 Full and Compact Output Packages 143 Tables for Full Output Package 144 Table for Compact Output Package 152 Helpful hints for transferring Agilent output files 156 XML output 156 TIFF Results 158 5 How Algorithms Calculate Results Overview of Feature Extraction algorithms 160 Algorithms and functions they perform 160 Algorithms and res
91. ed signal mean signal or dye normalized signal fhe Agilent Technologies 69 70 You have the option in the Project Properties sheet of selecting to generate either the FULL set of parameters statistics and feature information COMPACT QC or MINIMAL COMPACT output package is the default The COMPACT output package contains only those columns that are required by GeneSpring and DNA Analytics software The tables on the following pages present the text file summary for all output package types FULL COMPACT QC or MINIMAL Some of the parameters statistical results and feature results may not be included from any one output file depending on the application and protocol used for Feature Extraction You also have the option to generate one file with all three tables or three separate files with one for each table To select to generate one file or three see the Agilent Feature Extraction for CytoGenomics User Guide To display the text results file in an easy to read format see the Agilent Feature Extraction for CytoGenomics User Guide Feature Extraction for CytoGenomics Reference Guide Parameters options FEPARAMS The top most section of the result file contains the parameters and option choices that you used to run Feature Extraction FULL FEPARAMS Table Table 3 List of parameters and options contained within the FULL text output file FEPARAMS table Protocol Step Parameters Type Options Description P
92. edSigError LogRatio Result Definition A surface is fitted through the log of the background subtracted signal to look for multiplicative gradients A normalized version of that surface interpolated at each point of the microarray is stored in MultDetrendSignal The surface is normalized by dividing each point by the overall average of the surface That average is stored in MultDetrendSurfaceAverage as a statistic If the protocol uses the option to fit to only replicate features the surface is normalized for the fit The MultDetrend SurfaceAverage is smaller in this case a number around 1 A non zero surrogate value indicates that the MeanSignal is less than or not significant versus the background or the BGSubSignal is less than the Error where the Error is the Additive Error for all default Agilent Protocols A dye normalized signal calculated by multiplying the BGSubSignal with the appropriate DyeNormFactor A global constant to normalize the dye bias from all feature background subtracted signals LinearDyeNormFactor is calculated such that geometric mean intensity of the selected normalization features equals 1000 The signal left after all the Feature Extraction processing steps have been completed In the case of 1 color ProcessedSignal contains the Multiplicatively Detrended BackgroundSubtracted Signal if the detrending is selected and helps If the detrending does not help this column will contain the BackgroundSubtract
93. edSignal The universal or propagated error left after all the processing steps of the Feature Extraction process have been completed In the case of one color If multiplicative detrending is performed ProcessedSignalError contains the error propagated from detrending This is done by dividing the error by the normalized MultDetrendSignal Log of the ratio of rProcessedSignal over gProcessedSignal The log ratio indicates the level of gene expression in cyanine 5 labeled sample relative to cyanine 3 labeled sample Feature Extraction for CytoGenomics Reference Guide Table 18 Algorithms Protocol Steps and the results they produce continued Protocol Step Results Result Definition Compute Ratios pValueLogRatio P value indicates the level of significance in the differential expression of a gene as measured through the log ratio MicroRNA Analysis g TotalGeneSignal This signal is the sum of the total probe signals in the green channel per gene MicroRNA Analysis gTotalGeneError This error is the square root of the sum of the squares of the TotalProbeError Feature Extraction for CytoGenomics Reference Guide 169 XDR Extraction Process 170 What is XDR scanning The Agilent scanner can cover a dynamic intensity range greatly in excess of the range covered by a single scan Furthermore Agilent microarray features can produce signals that span a broader range of intensity than a single scan can cover Therefore you can us
94. eger 1 TwoColor 2 OneColor 3 CGH integer 1 True 2 False float text Description Maximum allowable fraction of features along any edge of the microarray that are non uniform before a grid placement warning Is given Maximum allowable fraction of features along any edge of the microarray that are not found before a grid placement warning is given Maximum allowable fraction of the local background regions on the microarray that are flagged as NonUniform before a grid placement warning Is given Minimum value for the standard deviation for the negative controls Minimum value for the reproducibility The Spikeln formulation to use for the Spikeln Calculation Different formulations will yield different expected values and different concentration values If True default the sign of the slope for the spikelns plot and its trend will be changed when the slope is detected to have the wrong sign This means the labelling was intentionally flipped and must be flipped back The PercentilelntensitySignal is calculated by the software on the r g ProcessedSignal showing the signal at a given percentile over the NonControl features This parameter is the percentile used for the calculation By default the value is set to 5 the software generates the 75 Signal value of the ProcessedSignals for all channels available Version of Feature Extractor 87 Table 3 List of parameters and options contained wit
95. eloped by Rosetta Biosoftware Once xdev is computed it is plugged back into Equation 2 where LogRatioError is derived Feature Extraction for CytoGenomics Reference Guide For more details on calculations with the propagation error model see the confidential Agilent technical paper on error modeling If the Propagation of Pixel Level Error Model is used then LogRatioError is computed from the following sources e Feature PixSDev red and green channels e Background Noise calculation is dependent upon the chosen BkSubMethod red and green channels Once the LogRatioError is computed it is plugged back into Equation 21 where xdev is derived Table 23 Summary Use of surrogates for calculations Case 1 R G Both channels use DyeNorm Signals Case 2 r G r rSurrogateUsed P value and log ratio are calculated as usual G gDyeNormSignal For signals not using surrogates g r DyeNormSignal g r ProcessedSignal hich is then used to calculate log ratio Case 3 R g R DyeNormSignal g gSurrogateUsed P value and log ratio are calculated as usual If r G gt 1 then Feature Extraction automatically sets LogRatio 0 and PvalueLogRatio 1 Case 4 r g Both channels use surrogates Feature Extraction automatically sets P value and log ratio are calculated as usual LogRatio 0 and pValueLogRatio 1 If R g lt 1 then Feature Extraction automatically sets For signals using surrogates LogRatio 0 and pV
96. elps If the detrending does not help this column will contain the BackgroundSubtractedSignal The universal or propagated error left after all the processing steps of Feature Extraction have been completed In the case of one color ProcessedSignalError has had the Error Model applied and will contain at least the larger of the universal UEM error or the propagated error If multiplicative detrending is performed ProcessedSignalError contains the error propagated from detrending This is done by dividing the error by the normalized MultDetrendSignal Number of outlier pixels per feature with intensity gt upper threshold set via the pixel outlier rejection method The number is computed independently in each channel These pixels are omitted from all subsequent calculations Number of outlier pixels per feature with intensity lt lower threshold set via the pixel outlier rejection method The number is computed independently in each channel These pixels are omitted from all subsequent calculations NOTE The pixel outlier method is the ONLY step that removes data in Feature Extraction Feature Extraction for CytoGenomics Reference Guide 117 Table 8 Feature results contained in the FULL output text file FULL FEATURES table continued Features Green gNumPix gMeanSignal gMedianSignal gPixSDev gPixNormlQR gBGNumPix gBGMeanSignal gBGMedianSignal gBGPixSDev gBGPixNormlQR gNumS
97. ely if the mean signal e g MeanSignal or BGMeanSignal is greater than the upper rejection boundary RBupper or less than the lower rejection boundary RBLower MeanSignal gt RB upper MeanSignal lt RB ower where RB Upper I vopercentile i CutoffPopOutlier and RB Upper I25percentile Cutoffpopoutlier Feature Extraction for CytoGenomics Reference Guide 189 Compute Bkgd Bias and Error Feature extraction completes several steps in order to determine the error model for each feature First it determines and subtracts the background for each feature on the array This is followed by detrending the array for systematic error Finally an error model accounts for systematic and random errors encountered during sample preparation hybridization and scanning steps Step 12 Calculate the feature background subtracted signal BGSubSignal The feature background subtracted signal BGSubSignal is calculated by subtracting a value called the BGUsed from the feature mean signal BGSubSignal MeanSignal BGUsed_ 11 where BGSubSignal and BGUsed depend on the type of background method and the settings for spatial detrend and global background adjust See the table below Table 20 Values for BGSubSignal BGUsed and BGSDUsed for different methods and settings Background Background SpDe OFF Spatial Detrend SpDe ON SpDe OFF Spatial Detrend ON Subtraction Subtraction Method Variable Global Bkgnd GBA OFF GBA ON Glob
98. eported to 9 decimal places in exponential notation for all result files Feature Extraction for CytoGenomics Reference Guide 113 Feature results FEATURES The bottom section of the text file gives descriptions of the results for each feature Results are reported to 9 decimal places in exponential notation for all result files FULL Features Table Table 8 Feature results contained in the FULL output text file FULL FEATURES table Features Green Features Red Types Options Description FeatureNum integer Feature number Row integer Feature location row Col integer Feature location column Accessions text Gene accession numbers Chr_coord text Chromosome coordinates of the feature Sub TypeMask integer Numeric code defining the subtype of any control feature Sub TypeName integer Name of the subtype of any control feature Start integer Indicates the place in the transcript where the probe sequence starts Sequence text The sequence of bases printed on the array ProbeUID integer Unique integer for each unique probe in a design 114 Feature Extraction for CytoGenomics Reference Guide Table 8 Feature results contained in the FULL output text file FULL FEATURES table continued Features Green Controllype Features Red Types integer Options Description Feature control type See XML Control ProbeName GeneName SystematicName Description PositionX PositionY text text
99. er integer integer integer float Description The average of the net signal of all inlier local backgrounds The average of all inlier local backgrounds The standard deviation of all inlier local backgrounds The number of inlier local backgrounds The average of all inliers used in background estimation for the selected global background subtraction method or the average of all inlier local backgrounds if the local background subtraction method is selected after global background adjustment is applied if selected The standard deviation of all inliers used in background estimation for the selected global background subtraction method or the standard deviation of all inlier local backgrounds if the local background subtraction method is selected The number of all inliers used in background estimation for the selected global background subtraction method or the number of all inlier local backgrounds if the local background subtraction method is selected The number of features that are flagged as non uniformity outliers The number of features that are flagged as population outliers The number of local background regions that are flagged as non uniformity outliers The number of local background regions that are flagged as population outliers Software estimated scanner offset 99 Table 7 Stats results contained in the text output file STATS table continued Stats Green Channel Stats Red Channe
100. er channel 118 Feature Extraction for CytoGenomics Reference Guide Table 8 Features Green glsSaturated glsLowPMT Scaled Up PixCorrelation BGPixCorrelation glsFeatNonUnifOL glsBGNonUnifOL Features Red rlsSaturated rlsLlowPMTScaled Up rlsFeatNonUnifOL rlsBGNonUnifOL Types boolean boolean float float boolean boolean Options 1 Saturated or 0 Not saturated 1 Low 0 High g r lsFeatNonUnifO L 1 indicates Feature is a non uniformity outlier in g r g r lsBGNonUnifOL indicates Local background is a non uniformity outlier in g r Feature Extraction for CytoGenomics Reference Guide Feature results contained in the FULL output text file FULL FEATURES table continued Description Boolean flag indicating if a feature is saturated or not A feature is saturated IF 50 of the pixels in a feature are above the saturation threshold Reports if the feature signal value is from the scaled up low signal image or from the high signal image Ratio of estimated feature covariance in RedGreen space to product of feature standard deviation in Red Green space The covariance of two features measures their tendency to vary together i e to co vary In this case it is a cumulative quantitation of the tendency of pixels belonging to a particular feature in Red and Green spaces to co vary The same concept as above but in case of background Boolea
101. er image per channel as measured by scanner Median dark offset per image per channel as measured by the scanner Standard deviation of the data points measured by the scanner to determine the dark offset per image per channel Number of points of data measured by the scanner to determine the dark offset per image per channel Signal intensity at which spot Is considered saturated The average ratio of net signal to local background for all spike in probes The average ratio of net signal to local background for all negative control probes The ratio of AvgSig2BkgeQC to AvgSig2BkgNegCtrl The number of saturated features on the microarray per channel Feature Extraction for CytoGenomics Reference Guide Table 7 Stats results contained in the text output file STATS table continued Stats Green Channel gLocalBGlnlierNetAve gLocalBGlnlierAve gLocalBGlnlierSDev gLocalBGlInlierNum gGlobalBGInlierAve gGlobalBGInlierSDev gGlobalBGInlierNum gNumFeatureNonUnifOL gNumPopnOL gNumNonUnifBGOL gNumPopnBGOL gOffsetUsed Feature Extraction for CytoGenomics Reference Guide Stats Red Channel rLocalBGlnlierNetAve rLocalBGInlierAve rLocalBGInlierSDev rLocalBGlnlierNum rGlobalBGInlierAve rGlobalBGInlierSDev rGlobalBGInlierNum rNumFeatureNonUnifOL rNumPopnOL rNumNonUnifBGOL rNumPopnBGOL rOffsetUsed Type float float float integer float float integer integ
102. erated from a 2 color gene expression extraction whose GE2 metric set with thresholds had been added In this extraction spatial and multiplicative detrending were turned off Note that not all values of the metrics are within the default thresholds QC Report Agilent Technologies 2 Color Gene Expression Date Saturday September 11 2010 01 42 BG Method No Background Image Hu22K_GE2_251209710036 Background Detrend Off Protocol GE2_1010_Sepi0_2 2 Editable Multiplicative Detrend False User Name Administrator Dye Norm Linear Lowess Grid 012097_D_20070820 Linear DyeNorm Factor 4 05 Red 6 84 Green FE Version 10 10 0 23 Additive Error 13 Red 28 Green Sample red green Saturation Value 65211 r 65185 g DyeNorm List No of Probes in DyeNorm List Evaluation Metrics for GE2_QCMT_Sep10 Good 10 Evaluate 2 Metric Name Value Excellent Good Evaluate IsGoodGrid gt i lt 1 AnyColorPrentFeatNonun lt 1 gt 1 gNegCtrlAveBGSubSig 20 to 10 lt 20 or gt 10 gNegCtriSDevBGSubSig lt 15 gt 15 rNegCtrlAveBGSubSig 20 to 4 lt 20 or gt 4 rNegCtriSDevBGSubSig lt 6 gt 6 gNonCntriMedCVBkSubSig Oto18 lt Oor gt 18 rNonCntriMedCVBkSubSig Otoi8 lt Oor gt 18 gE1aMedCvBkSubSignal Oto1i8 lt Oor gt 18 rE1aMedCVvBkSubSignal Oto1i8 lt Oor gt 18 absE1aObsVsExpCorr gt 0 86 lt 0 86 absE1aObsVsExpSlope gt 0 85 lt 0 85 Excellent Good Evaluate Figure 4 QC Report Header and Evaluation Metrics with GE2 metric set with
103. error on log ratio of feature PvalueLogRatio and LogRatioError on page 215 of this guide Feature Extraction for CytoGenomics Reference Guide Index Numerics 1 color detrend algorithm 208 A algorithms how calculate results 174 overview 160 results they produce 166 annotations public accession numbers 139 C compute ratios and errors calculate feature log ratio 215 calculate processed signal 215 calculate pvalue and log ratio error 215 calculate surrogate value 207 control types 157 correct bkgd and signal biases calculate background subtracted feature signal 190 calculate significance 205 how background adjustment works 198 how multiplicative detrend algorithm works 1 color only 208 values for BGSubSignal BGUsed and BGSDUsed 190 correct dye biases calculate normalization factor 212 select normalization features 210 E example calculations 220 F feature flag info conversion of 157 features results 114 file format options 158 find and measure spots calculate mean signal of feature 182 calculate mean signal of local background 183 define features 178 estimate local background radius 178 reject pixel outliers 181 saturated features 183 flag outliers non uniformity 184 population 186 G GEML result file feature results 146 152 L log ratios from adjusted background subtracted signals 200 from unadjusted background subtracted signals 199 M MAGE ML form
104. es method Under this method the initial normalization features are selected based on the following three criteria Feature Extraction for CytoGenomics Reference Guide e Features are positive and significant versus the background e g IsPosAndSignif 1 e Features are non control e g ControlType 0 e Features are non outlier e g IsFeatNonUnifOL 0 IsFeatPopnOL 0 IsSaturated 0 Using List of Normalization Genes method Under this method the user selects the normalization features These features can be housekeeping genes or genes with no differential expression Using Rank Consistency Probes method Under this method the chosen normalization features simulate housekeeping genes These features fall within the central tendency of the data having consistent trends between the red and green channels They are selected based on the following two criteria e Features pass the three criteria described in the all significant non control and non outlier features method and e Features pass the rank consistency filter between the red and green channels Rank consistency filter is done by transforming the feature BGSubSignal to feature rank per channel Next the feature correlation strength is calculated per feature CS Pr Pal 25 N where pp and pg are the ranks of feature in the red and green channels respectively where N is the total number of initial normalization features If the CS l
105. es above the blue squares represent the low intensity features found on the array In the absence of a moving window the lowest features on the entire array are located and may exhibit spatial bias With the moving window the lowest features from each region of the microarray are better identified e OnlyNegativeControlFeatures Feature Extraction for CytoGenomics Reference Guide This selection fits the surface to the negative control features distributed on the slide and is recommended for Agilent CGH microarrays This option works well with well defined negative controls Outlier filtering should be enabled with this option to ensure good negative control values To enable outlier filtering set NegCtrlSpread Outlier Rejection On to True which removes artifacts from distorting the control feature set distribution This is illustrated in the following figure The purple surface represents a smoothed fit to all the negative control feature inliers The residual of the surface fit is the Error on background subtraction in the Additive Error Estimation see Step 16 Determine the error in the signal calculation on page 202 Feature Extraction for CytoGenomics Reference Guide 193 194 e FeaturesInNegativeControlRange This algorithm does two levels of filtering First it finds the features in the range of negative controls by fitting the negative controls to a surface and finding non control features whose signal is w
106. es generated after Feature Extraction 5 How Algorithms Calculate Results Learn how Feature Extraction algorithms calculate the results that help you interpret your gene expression experiments 6 Command Line Feature Extraction This chapter contains the commands and arguments to integrate Feature Extraction into a completely automated workflow Feature Extraction for CytoGenomics Reference Guide Acknowledgments Apache acknowledgment Part of this software is based on the Xerces XML parser Copyright c 1999 2000 The Apache Software Foundation All Rights Reserved www apache org JPEG acknowledgment This software is based in part on the work of the Independent JPEG Group Copyright c 1991 1998 Thomas G Lane All Rights Reserved Loess Netlib acknowledgment Part of this software is based on a Loess Lowess algorithm and implementation The authors of Loess Lowess are Cleveland Grosse and Shyu Copyright c 1989 1992 by AT amp T Permission to use copy modify and distribute this software for any purpose without fee is hereby granted provided that this entire notice in included in all copies of any software which is or includes a copy or modification of this software and in all copies of the supporting documentation for such software THIS SOFTWARE IS BEING PROVIDED AS IS WITHOUT ANY EXPRESS OR IMPLIED WARRANTY NEITHER THE AUTHORS NOR AT amp T MAKE ANY REPRESENTATION OR WARRANTY OF ANY KIND CONCERNING TH
107. etrend 1400 BO mt Count m oO fom N o r N dada eh ESSSrH EPPEN Ebek Neree SFNeFE NS VYrrr Reig gn PT CRan gi nterpolatedNegCtnSubSignal The effects of using all features for detrending shown in the left figure as compared to using the features in the negative control range shown in the right figure Features that had detrending added are shown in blue The FeaturesInNegativeControlRange algorithm more accurately centers the values around zero A 2D Loess algorithm fits the surface on the mean intensities of the filtered low intensity features of both red and green channels separately This is described graphically in the figure below Feature Extraction for CytoGenomics Reference Guide 195 eMeanSignal gSpatialDetrendSurface alue The effect of a 2 dimensional Loess fit to the green mean signal intensities across the array You can find more information on the algorithm from the Web site http www itl nist gov div898 handbook pmd section1 pmd144 htm If N number of data points selected for surface fitting after filtering and J gin point from the filtered low intensity data set the Loess algorithm fits a surface through these data points to obtain an intensity value describing the surface corresponding to each input data point Let O denote the fitted output surface corresponding to the ih input point J The statistical results that come out of this calculation are described in the table on
108. etting Value v10 10 0 700 185k 185k 10 uM 244k 10 uM 65 micron feature size 0 750 30 micron feature size Hidden if Array Format is set to Automatically Determine 1 200 All Formats except 30 micron feature size 1 300 30 micron feature size Hidden if Array Format is set to Automatically Determine True Single Density Double Density 25k 95k False 185k 185k 10uM 65 micron feature size 30 micron feature size 244k 10uM Hidden if Array Format is set to Automatically Determine 100 when False for 185k 185k 10uM 65 micron feature size 244k 10 uM 150 when False for 30 micron feature size Inter Quartile Region Automatically Determine and All Formats 1 42 All Formats 1 42 All Formats Use Mean Standard Deviation Automatically Determine and All Formats True 10 16 Feature Extraction for CytoGenomics Reference Guide Table 1 Default settings for the preloaded CGH protocols Protocol Step Parameter lORatio Background ORatio Use Otest for Small Populations Report Population Outliers as Failed in MAGEML file Compute Non Uniform Outliers Scanner The values for the parameters change depending on the scanner used for the image See below for differences Agilent scanner Automatically Compute OL Polynomial Terms Feature CV 2 Red Poissonian Noise Term Multiplier Red Signal Constant Term Multiplier Green Poissonian Noise Term Multiplier Green
109. feature passes g r lsPosAndSignif and additionally the g r BGSubSignal is greater than 2 6 g r BG_SD You can change the multiplier 2 6 138 Feature Extraction for CytoGenomics Reference Guide Other text result file annotations The following public accession numbers may or may not show up in the Feature Results section of the output text file Table 12 Public accession numbers in the output text file Abbreviation dbj emb gb gbpri gi gp mgi pdb pir prf rafl ref Sp tair ug Description DNA Database of Japan EMBL GenBank GenBank primate nucleotide accession number GenBank Gene Identifier GenPept protein identification number Mouse Genome Informatics Brookhaven Protein data bank NBRF PIR Protein Research Foundation RIKEN full Length cDNA RefSeq SwissProt The Arabidopsis Information Resource UniGenelocuslink LocusLink ID Whitehead Feature Extraction for CytoGenomics Reference Guide 139 140 Feature Extraction for CytoGenomics Reference Guide Agilent CytoGenomics 3 0 Agilent Feature Extraction for CytoGenomics Reference Guide 4 MAGE ML XML File Results How Agilent output file formats are used by databases 142 MAGE ML results 143 Helpful hints for transferring Agilent output files 156 This chapter provides a listing of MAGE ML results in the form of tables Refer to these tables when you want to know the results reported in a particular file This chapter also contains a secti
110. float Bias and Error Compute Bkgd BGSubtractor BackgroundCorrectionO integer Bias and Error n 1 True 0 False Compute Bkgd BGSubtractor_BgCorrectionOffset Bias and Error Compute Bkgd BGSubtractor_CalculateSurface integer Bias and Error MetricsOn 1 True 0 False Feature Extraction for CytoGenomics Reference Guide Description Either minimum feature or minimum local background across the microarray for background subtraction global method Average of local backgrounds for background subtraction global method Average of negative controls for background for background subtraction global method Local background corresponding to each feature for background subtraction local method Minimum feature across the microarray for background subtraction global method No background subtraction The pValue at which a feature is determined to be statistically significant above background The number of standard deviations above background at which the feature is flagged as well above background Globally adjust background turned on Globally adjust background turned off Adjust the signal of all features by an offset constant so that very low signal features end up at this offset Appears when Globally adjust background is turned on Surface fit is done and metrics calculated Surface fit and metrics are not done 81 Table 3 Protocol Step Compute Bkgd Bias and Error Compute Bkgd Bias a
111. for CytoGenomics Reference Guide PixSDev OE M MeanSignal MinSig 4rray 8 where B or O Conin is the term that estimates the sources of variance that are proportional to the square root of the signal including scanning measurement or counting error the variance follows a Poisson distribution This term is dependent on the intensity and the scan resolution of the image where C or o Noise 1S the term that estimates the sources of variance that are independent of the signal including electronic noise in scanner and background level noise in glass the variance is a Constant The variables A B and C have different values for feature and background For Agilent data produced with the GE2 SSPE_95_Feb07 protocol these values are determined empirically default selection in protocol from self vs self experiments and from the known noise characteristics of the Agilent Microarray system discussed above For all other Agilent Feature Extraction protocols only the A term is empirically determined For all other Agilent protocols the default selection in the protocol is to determine the B and C terms automatically Here is how the Feature Extraction program calculates these terms e Saturated features are omitted from the population of negative control probes NC This NC set and the local background regions associated with these features are used in the calculations e Calculates Net Signal e Calculates the pixel standard
112. g the original R and G R R 10MFit 2 and G 1oMFitY 2 d If the original log ratio is exactly along the fit line Mfit the new log ratio is shifted to zero If log R G Mfit then Log R Log G Mfit or Log R 10MF 2 Log G 10MFI Mfit or Log R Mfit 2 Log G Mfit 2 Mfit or Log R G 0 e The LOWESSDyeNormFactor for R is 1 10 The LOWESSDyeNorm Factor for G is 10M 7 2 Linear amp LOWESSDyeNormFactor This curve fitting algorithm does a linear scaling normalization of the data individually in each channel before performing a non linear dye normalization The Linear amp LOWESS dye normalization factor can be calculated from the equation below DyeNormalSignal 27 BGSubSignal x LinearDyeNormFactor Feature Extraction for CytoGenomics Reference Guide 213 Step 23 Determine if surrogate values must substitute for low intensity signals At this point two criteria are used to determine is surrogate values must take the place of the low intensity signals e The feature signal is not positive and significant versus background e The signal is not larger than the background error Surrogate values were computed during background subtraction and are stored in the SurrogateUsed column Step 24 Calculate the dye normalized signal DyeNormSignal The dye normalized signal is calculated by multiplying the background subtracted signal by the dye normalization factor DyeNormS
113. gSurrogateUsed rSurrogateUsed Description Found coordinates of the feature centroid Diameter of the spot X or Y Axis log REDsignal GREENsignal per feature processed signals used to calculate log ratio If SURROGATES are turned off then if DyeNormRedSig lt 0 0 amp DyeNormGreenSig gt 0 0 if DyeNormRedSig gt 0 0 amp DyeNormGreenSig lt 0 0 if DyeNormRedSig lt 0 0 amp DyeNormGreenSig lt 0 0 If SURROGATES are turned off then if DyeNormRedSig lt 0 0 OR DyeNormGreenSig lt 0 0 IF SURROGATES are turned on then LogRatioError error of the log ratio calculated according to the error model chosen Significance level of the Log Ratio computed for a feature The g r surrogate value used No surrogate value used Feature Extraction for CytoGenomics Reference Guide Table 15 Feature results Full contained in the MAGE ML FEATURES table Quant Features Green Type SOT glsFound Derived Green DerivedSignal Signal Error Green ProcessedSig Error SQT gNumPixOLHi SOT gNumPixOLLo SOT gNumPix Features Red Options 1 IsFound 0 IsNotFound rlsFound Red DerivedSignal Red ProcessedSig Error rNumPixOLHi rNumPixOLLo rNumPix Feature Extraction for CytoGenomics Reference Guide Description A boolean used to flag found strong features The flag is applied independently in each channel A feature is considered found if the calculated spot cen
114. ge i e IQR of the population SQT glsBGPopnOL rlsBGPopnOL g r IsBGPopnOL 1 The same concept as above but for indicates local background background is a population outlier in g r SOT IsManualFlag SOT gBGSubSignal rBGSubSignal gBGSubSignal Background subtracted signal gMeanSignal To display the values used to calculate gBGUsed this variable using different background signals and settings of spatial detrend and global background adjust see Table 20 on page 190 Error gBGSubSigError rBGSubSigError Propagated standard error as computed on net g r background subtracted signal SOT BGSubSigCorrelation Ratio of estimated background subtracted feature signal covariance in RG space to product of background subtracted feature Standard Deviation in RG space 150 Feature Extraction for CytoGenomics Reference Guide Table 15 Feature results Full contained in the MAGE ML FEATURES table Quant Features Green Type SOT glsPosAndSignif SQT gPValFeatEqBG SQT glsWellAboveBG Boolean gSpatialDetrendlsIn FilteredSet float gSpatialDetrend SurfaceValue SOT IsUsedBGAdjust SOT gBGUsed Features Red Options rlsPosAndSignif g r isPosAndSignif 1 indicates Feature is positive and significant above background rPValFeatEqBG rlsWellAboveBG rSpatialDetrendlsIn FilteredSet rSpatialDetrend SurfaceValue 1 Feature used 0 Feature not used rBGUsed gBGSubSignal gMeanSignal gBGUsed SQT Speci
115. ger integer true 1 false 0 float 0 00 1 00 0 70 default Description Multiplier parameters for feature outlier rejection method as selected above Multiplier parameters for background outlier rejection method as selected above Different algorithms to calculate spot statistics CookieCutter method Whole Spot method The fraction of the nominal radius used to draw the cookie around the centroid of each spot The outer radius of the exclusion zone based on nominal spot size The option to calculate the outer radius of the local background based on row and column spacing The outer radius of the local background supplied from the protocol if EstimateLocalRadius is not selected The option for the statistical method for determining signals from features either mean and standard deviation or median and normalized IQR Mean is 1 and Median is 2 The option to set whether the program computes and shows the skew of each feature Default is false The percentage of the feature that should be used when calculating the pixel skew A value of 0 means 70 of the radius of the feature Feature Extraction for CytoGenomics Reference Guide Table 3 List of parameters and options contained within the FULL text output file FEPARAMS table Protocol Step Find Spots Find Spots Flag Outliers Flag Outliers Flag Outliers Flag Outliers Flag Outliers Flag Outliers Flag Outliers Flag O
116. gnal if rSurrogate Used 49209 6 49209 6 Feature Extraction for CytoGenomics Reference Guide 223 rSurrogateUsed rBGSDUsed if Use Pixel Statistics for Significance is selected If a feature fails either or both of the criteria above SurrogateUsed is a non zero value and is calculated as shown below depending on the Significance test parameter chosen in the Compute Bkgd Bias and Error protocol step rSurrogateUsed rAddError rLinearDyeNormFactor if Use Error Model for Significance is selected If a surrogate is used in the red channel i e rSurrogateUsed is a non zero value the red processed signal is calculated as surrogate value multiplied by the dye normalization factors rProcessedSignal rSurrogateUsed rLinearDyeNormFactor rLowessDyeNormFator if rSurrogateUsed 0 224 The Log ratio is the log of red processed signal over green processed signal rProcessedSignal gProcessedSignal 0 0308612 log 49209 64 45834 13 LogRatio log It is important to note that log ratio and p value calculations are computed differently depending on whether a surrogate is used in only one channel both channels or neither channels If a feature uses a surrogate in only the red channel Case 2 of Table 23 and the red surrogate value is not greater than the green processed signal the p value and error on the log ratio are calculated as usual using equations 1 and 2 in Step 27 Calculate the p value and
117. gnal lower limit of detection min step a eQCOneColorLogLowSignal error for lower limit See equation below table eQCOneColorLogLowSignalError lowest quantifiable signal lowest signal from linear eQCOneColorLinFitLogLowSignal in linear range fit in step h highest quantifiable signal highest signal from linear eQCOneColorLinFitLogHighSignal in linear range fit in step h lowest concentration x0 2 3w in step f eQCOneColorLinFitLogLowConc leading to quantifiable signal Feature Extraction for CytoGenomics Reference Guide Table 2 Spike In Concentration Response Statistics for 1 color microarrays Statistic Description Where in calculations Stats Table Output High Relative Concentration highest concentration x0 2 2w in step g eQCOneColorLinFitLogHighConc leading to quantifiable signal Slope slope of the linear fit on from step h eQCOneColorLinFitSlope sigmoidal curve R 2 Value correlation coefficient for from step h eOQCOneColorLinFitRSO linear fit Spikeln Detection Limit The average plus 1 from step eQCOneColorSpikelnDetectionLi standard deviation of the mit spike ins below the linear concentration range LowThresholdError y SD Log ProcessedSignals A where the set A is from step a in the table Feature Extraction for CytoGenomics Reference Guide 57 58 Accuracy of linear fit to middle of sigmoidal curve Agilent calculated the difference between expected log processed signals at the high and low relative concentratio
118. gradient N pa N 14 Step 14 Adjust the background This algorithm determines the offset in both the red and green channels by identifying features that are not differentially expressed and fall within the central tendency of the data especially in the lower intensity domain These features should not be saturated or be flagged as non uniform outliers Using this method yields more accurate and reproducible background subtracted signals and log ratios for two channel data than using no correction or single channel correction Using a self self microarray i e same target labeled in red and green channels one expects to see a linear plot of red background subtracted signal versus green If the backgrounds have not been estimated correctly in one channel with respect to the second channel there will be a bias This bias yields a hook at the low end of the signal range when shown in a plot with log scale axes see Figure 47 Feature Extraction for CytoGenomics Reference Guide 50000 10000 rBGSubSignal z 1 10 100 1000 10000 qBGSubSignal Figure 47 Unadjusted background subtracted signals The background adjustment algorithm first finds the central tendency of the data features shown as blue circles in the figures Using this subset of features the algorithm then estimates the best adjustment in both the red and green channels to remove the bias After the background adjustment the bias is removed
119. ground signals and settings of spatial detrend and global background adjust see Table 20 on page 190 Propagated standard error as computed on net g r background subtracted signal For one color the error model is applied to the background subtracted signal This will contain the larger of he universal UEM error or the propagated error Ratio of estimated background subtracted feature signal covariance in RG space to product of background subtracted feature standard deviation in RG space 120 Feature Extraction for CytoGenomics Reference Guide Table 8 Feature results contained in the FULL output text file FULL FEATURES table continued Features Green glsPosAndSignif gPValFeatEqBG gNumBGUsed glsWellAboveBG gBGUsed gBGSDUsed IsNormalization Features Red rlsPosAndSignif rPValFeatEqBG rNumBGUsed rlsWellAboveBG rBGUsed rBGSDUsed Types Boolean float integer Boolean float float boolean Options g r isPosAndSignif 1 indicates Feature is positive and significant above background g r BGSubSignal g r MeanSignal g r BGUsed 1 Feature used 0 Feature not used Feature Extraction for CytoGenomics Reference Guide Description Boolean flag established via a 2 sided t test indicates if the mean signal of a feature is greater than the corresponding background selected by user and if this difference is significant To dis
120. hin the FULL text output file FEPARAMS table Protocol Step Parameters Type Options Description FeatureExtractor_Single TextFile integer Output 1 True The system prints the three tables FEParams Stats and Features are printed 0 False in the same text file The system prints each of the three tables in separate text files FeatureExtractor_JPEGDownSample float Factor by which the image is scaled down Factor and then converted to the JPEG format Must be at least 2 1 is no longer allowed FeatureExtractor _ColorMode integer A flag to indicate output color 0 One color green only 1 2 color 2 One color red only FeatureExtractor_QCReportType integer Type of QC report to generate 0 Gene Expression 1 CGH_ChIP 2 miRNA 4 Streamlined CGH FeatureExtractor OutputQCReport integer Generate output details on OC report GraphText 1 True graphs 0 False 88 Feature Extraction for CytoGenomics Reference Guide COMPACT FEPARAMS Table Table 4 List of parameters and options contained within the COMPACT text output file FEPARAMS table Protocol Step Parameters Protocol Name Protocol date Scan_ScannerName Scan_NumChannels Scan_date Scan_MicronsPerPixelX Scan_MicronsPerPixelY Scan_OriginalGUID Scan_NumScanPass Grid_Name Grid_Date Grid_NumSubGridRows Grid_NumSubGridCols Grid_NumRows Grid_NumCols Grid_RowSpacing Grid_ColSpacing Grid_OffsetX Type Options text text text integer text floa
121. id_Name Grid_Date Grid_NumSubGridRows Grid_NumSubGridCols Grid_NumRows Grid_NumCols Grid_RowSpacing Grid_ColSpacing Grid_OffsetX Feature Extraction for CytoGenomics Reference Guide Type Options text text text integer text float float text 1 or2 text integer integer integer integer integer float float float Description Name of protocol used Date the protocol was last modified Agilent scanner serial number used Number of channels in the scan image Date the image was scanned Number of microns per pixel in the X axis of the scan image Number of microns per pixel in the Y axis of the scan image The global unique identifier for the scan image For 5 micron scans indicates whether the scan mode was a single 1 or double pass scan mode on the Agilent Scanner Grid template name or grid file name Date the grid template or grid file was created Number of subgrid columns Number of subgrid columns Number of spots per row of each subgrid Number of spots per column of each subgrid Space between rows on the grid Space between column on the grid In a dense pack array the offset in the X direction 95 Table 6 List of parameters and options contained within the MINIMAL text output file FEPARAMS table Protocol Step 96 Parameters Grid_OffsetY Grid_NomSpotWidth Grid_NomSpotHeight Grid_GenomicBuild FeatureExtractor_Barcode FeatureExtractor_ Samp
122. ignal BGSubSignal x DNF 28 where DNF LinearDyeNormFactor when linear dye normalization method is used and where DNF LinearDyeNormFactor x LOWESSDyeNormFactor 29 when LOWESS dye normalization method is used 214 Feature Extraction for CytoGenomics Reference Guide Compute Ratios Step 25 Calculate the processed signal ProcessedSignal The processed signal is used in calculating the log ratio If a surrogate is not used i e SurrogateUsed zero value then the processed signal is the dye normalized signal If a surrogate is used i e SurrogateUsed non zero value then the processed signal is the SurrogateUsed value if SurrogateUsed 0 then ProcessedSignal DyeNormSignal if SurrogateUsed 0 then ProcessedSignal SurrogateUsed DyeNormF actors where DyeNormFactors LinearDyeNormFactor LowessDyeNormF actor if Linear and Lowess methods are used Step 26 Calculate the log ratio of feature LogRatio The log ratio 2 is the measure of differential expression between the red and green channels for every probe 2 ProcessedSignal Logkatio Logio 30 ProcessedSignal where ProcessedSignal and ProcessedSignal are signals post dye normalization and post surrogate processing in the red and green channels respectively Step 27 Calculate the p value and error on log ratio of feature PvalueLogRatio and LogRatioError PvalueLogRatio gives the statistical significance on the log rati
123. ined in the text output file STATS table continued Stats Green Channel EffectiveFeatureSizeFraction Feature UniformityAnomaly Fraction UsedDefaultEffectiveFeature Size gPercentilelntensityProcessed Signal glotalSignal99pctile gNegCtrlSpread 110 Stats Red Channel rPercentilelntensityProcessed Signal rNegCtriSpread Type float float integer float float float Description Estimates the ratio of the effective feature size to the nominal feature size It is calculated by looking at the ratio of the whole spot measurement versus the cookie measurement Fraction Num TotalNum of the number of features looked at that had anomalous ratios This gives a measure of the percentage of representative spots that are strange e g donuts super hot spots hot crescents Reports whether or not the default effective feature size was used If the default was used the stat is 1 If the effective feature size was estimated the stat value is 0 The protocol lets you enter the Percentile Value at which the intensity of the noncontrol signals is recorded All protocols specify the 75th percentile This number is the intensity of all the noncontrol signals in the 75th percentile This stat is used to normalize 1 color data These are metrics for miRNA only This is the value of the TotalGeneSignal for all genes at the 99th percentile The root mean square RMS of the preliminary spatial
124. itation Type Feature Extraction for CytoGenomics Reference Guide g r isPosAndSignif 1 indicates Feature is positive and significant above background Description Boolean flag established via a 2 sided t test indicates if the mean signal of a feature is greater than the corresponding background selected by user and if this difference is significant To display variables used in the t test see Table 20 on page 190 Boolean flag indicating if a feature is WellAbove Background or not Feature passes g r lsPosAndSignitf and additionally the g r BGSubSignal is greater than 2 6 g r BGSDUsed 155 Helpful hints for transferring Agilent output files XML output There are several situations you should be aware of as you use MAGE ML XML output with gene expression data analysis software from Rosetta BioSoftware Rosetta Resolver software If there is no barcode If there is no barcode in the original tif file for whatever reason there will be no barcode information in the MAGE ML output warning message in Project Run summary For the data to load into Rosetta Resolver it must have a barcode associated with it You can add barcode information in the Scan Image Properties dialog box See the Agilent Feature Extraction for CytoGenomics User Guide Access control list ACL Rosetta Resolver knows about the access control list ACL assigned to the scan and can easily recognize and load any MAGE ML file The owner of
125. ithin 3 standard deviations of that fit Then it fits a Lowess curve to this set of features It interpolates from that fit to calculate a background signal for each feature For high density microarrays this algorithm can take a long time to complete its calculations To speed up the process you can elect in the protocol to randomly select a small percentage of the total points with which to calculate the fit To do this you set Perform Filtering for Fit to True which significantly reduces the amount of time for spatial detrending of high density microarrays 3 Residuals 3 Residuals N The purple surface represents the smoothed fit of all features plus or minus 3 errors of the negative control fit The residual of the surface fit is the Error on background subtraction in the Additive Error Estimation see Step 16 Determine the error in the signal calculation on page 202 Feature Extraction for CytoGenomics Reference Guide The FeaturesInNegativeControlRange algorithm has been shown to more accurately estimate zero than the All Feature Types background algorithm This improvement is shown below by viewing the features used in the additive detrend algorithm colored in blue superimposed on the InterpolatedNegCtrlSubSignal distribution You can see that the signals of those features are closer to zero when the FeaturesInNegativeControlRange algorithm is used AllDetrend FeatInNCRange 1600 Color by glnFitAddD
126. ities of all inlier pixels that represent the feature after outlier pixel rejection The number of inlier pixels is shown in the column NumPix Find Spots BGMeanSignal Average raw signal of the local background calculated from intensities of all inlier pixels that represent the local background of the feature after outlier pixel rejection The number of inlier pixels is shown in the column BGNumPix Find Spots BGMedianSignal Median raw signal of the local background calculated from intensities of all inlier pixels that represent the local background of the feature after outlier pixel rejection The number of inlier pixels is shown in the column BGNumPix Find Spots NetSignal MeanSignal minus Dark Offset Find Spots IsSaturated A Boolean flag of 1 indicates that the feature is saturated at least 50 of the inlier pixels in the feature have intensities above the saturation threshold One can determine the saturation level of a feature by dividing the NumSatPix by the NumPix Flag Outliers IsFeatureNonUnifOL A Boolean flag of 1 indicates that the feature is a non uniformity outlier the measured feature pixel variance is greater than the expected feature pixel variance plus the confidence interval Flag Outliers IsFeatPopOL A Boolean flag of 1 indicates that the feature is a population outlier This means that the feature MeanSignal is greater than the upper rejection boundary or less than the lower rejection boundary both of which are de
127. l gGlobalFeatinlierAve rGlobalFeatinlierAve gGlobalFeatInlierSDev rGlobalFeatInlierSDev gGlobalFeatinlierNum rGlobalFeatInlierNum AllColorPrentSat AnyColorPrentSat AnyColorPrentFeatNonUnifOL AnyColorPrentBGNonUnifOL AnyColorPrentFeatPopnOL AnyColorPrentBGPopnOL TotalPrcntFeatOL gBGAdjust rBGAdjust gNumNegBGSubFeat rNumNegBGSubFeat Type float float float float float float float float float float float integer Description Average of all inlier features Standard deviation of all inlier features Number of all inlier features The percentage of features that are saturated in both the green AND red channels The percentage of features that are saturated in either the green or red channel The percentage of features that are feature non uniformity outliers in either channel The percentage of local backgrounds that are non uniformity outliers in either channel The percentage of features that are population outliers in either the green or red channel The percentage of local backgrounds that are population outliers in either channel The percentage of non control features that are feature non uniformity outliers in either the green or red channel or are saturated in both channels Background offset constant to adjust all feature signals If Adjust Background Globally is set True all feature signals are adjusted by this offset If set to the value entered in the protocol all fea
128. l above background if its signal is 5 times the additive error SDpg is the background standard deviation i e BGSDUsed For the Error model significance test the SD becomes AddError 2 6 If the background subtracted signal is greater than the WellAboveSDMulti x SDpg and if the feature passes the IsPosAndSignif test then the feature gets a Boolean flag of 1 under the IsWellAboveBG column in Feature Extraction result file Step 19 Calculate the surrogate value SurrogateUsed The surrogate value is calculated and used as the lowest limit of detection to replace the dye normalized signal when any of the following situations occur These tests are done for each channel e MeanSignal is less than BGUsed or not significant compared to BGUsed i e IsPosAndSignif 0 e BGSubSignal is less than its background standard deviation 1 e BGSubSignal lt BGSDUsed The decision to replace a dye normalized signal with a surrogate value is not made however until after probes are selected for correcting the dye bias The surrogate value is calculated in this step using these criteria If pixel significance is used to calculate IsPosAndSignif then Feature Extraction for CytoGenomics Reference Guide 207 208 SurrogateUsed SDgg 19 where SDzg is the background standard deviation i e BGSDUsed For the local background method the standard deviation of the background is at the pixel level of the local backgroun
129. le Protocol Step Parameters Type Options Description FeatureExtractor_ColorMode integer A flag to indicate output color 0 One color green only 1 2 color FeatureExtractor QCReportlype integer Type of OC report to generate 0 Gene Expression 1 CGH_ChIP 2 miRNA 4 Streamlined CGH DyeNorm_NormFilename text Name of the dye normalization list file DyeNorm_NormNumProbes integer Number of probes in the dye normalization list Grid_IsGridFile boolean Feature Extraction for CytoGenomics Reference Guide 97 Statistical results STATS This middle section of the text file describes the results from the global array wide statistical calculations The STATS results are reported to 9 decimal places in exponential notation for all results files FULL COMPACT QC or MINIMAL STATS Table ALL text output types Table 7 Stats results contained in the text output file STATS table Stats Green Channel gDarkOffsetAverage gDarkOffsetMedian gDarkOffsetStdDev gDarkOffsetNumPts gSaturationValue gAvgSig2BkgeQC gAvgSig2BkgNegCtrl gRatioSig2BkgeQC_NegCtrl gNumSatFeat 98 Stats Red Channel rDarkOffsetAverage rDarkOffsetMedian rDarkOffsetStdDev rDarkOffsetNumPts rSaturationValue rAvgSig2BkgeQC rAvgSig2BkgNegCtrl rRatioSig2BkgeQC_NegCtrl rNumSatFeat Type float float float integer integer float float float integer Description Average dark offset p
130. le FeatureExtractor ScanFileName FeatureExtractor_ArrayName FeatureExtractor_ScanFileGUID FeatureExtractor_DesignFileName FeatureExtractor_Extractionlime FeatureExtractor UserName FeatureExtractor_ComputerName FeatureExtractor_Version FeatureExtractor_IsXDRExtraction Type Options float float float text text text text text text text text text text text integer 1 True 0 False Description In a dense pack array the offset in the Y direction Nominal width in microns of a spot from grid Nominal height in microns of a spot from grid The build of the genome used to create the annotation if available If the genome build is not available not all designs have this information then it is not put out All recent and all future designs have it Barcode of the Agilent microarray read from the scan image Names of hybridized samples red green Name of the scan file used for Feature Extraction Microarray filename GUID of the scan file Design or grid file used for Feature Extraction Time stamp at the beginning of Feature Extraction Windows Log In Name of the User who ran Feature Extraction Computer name on which Feature Extraction was run Version of Feature Extractor Says if result is from an XDR extraction Feature Extraction for CytoGenomics Reference Guide Table 6 List of parameters and options contained within the MINIMAL text output file FEPARAMS tab
131. les further reduces the size Feature Extraction for CytoGenomics Reference Guide 143 144 of the file to decrease the transfer time Use both Compact and Compressed MAGE ML files for Resolver The Compact package contains only those columns required by Resolver GenesSpring CGH Analytics and Chip Analytics In the Compact version of the MAGE ML file the entire FEPARAMS section is included MAGE ML has a rich mechanism for describing protocols and protocol parameters Tables for Full Output Package Table 13 Scan protocol parameters in MAGE ML result file Parameter Image acquisition identifier Log information Activity date Scanner information Operator ScanNumber Red LASER_POWER_VALUE Green LASER_POWER_VALUE Red PMT_GAIN_VALUE Green PMT_GAIN_VALUE Red Saturation_ Value Green Saturation_Value MICRONS PER_PIXEL_X Description Barcode or identifier for microarray Warnings and errors during run Time stamp for scanner run Information such as name make model and serial number of scanner Person that runs scanner Number of the scan associated with the values listed in this table Value of laser power in red channel Value of laser power in green channel Photomultiplier gain in red channel Photomultiplier gain in green channel Signal value beyond which signal is saturated in the red channel Signal value beyond which signal is saturated in the green channel Radius of pixel in the x direction Fea
132. licate features on the microarray Non uniformity outlier flagging is based on statistical deviation from the expected noise in the Agilent microarray based system scanner labeling hybridization protocols and microarrays The algorithm automatically calculates the B linear and C constant terms of the Feature Extraction for CytoGenomics Reference Guide polynomial fit for the expected noise for any type of microarray experiment Compute Bkgd Bias and Error This algorithm applies background subtraction to each feature to yield the background subtracted intensity You can also apply a spatial detrend algorithm to estimate and remove noise due to a systematic gradient on the microarray Another algorithm can correct for any underestimation or overestimation of the background in both the red and green channels of low intensity signals by applying a global background adjustment value to the background subtracted signals Before using the algorithm for estimating the error the system uses an algorithm to calculate robust negative control statistics for both CGH and miRNA data CGH microarrays have a variety of sequences that are used as negative controls Occasionally hot features are not flagged as population outliers In addition hot sequences may exist that is all features of that sequence have higher signals than features in other negative control sequences These problems can inflate NegC SD which is u
133. ll positive signals All negative and positive signals Methods for computation of dye normalization factor to remove dye bias Linear Linear amp LOWESS locally weighted linear regression preceded by linear scaling in each dye channel LOWESS locally weighted linear regression 85 Table 3 List of parameters and options contained within the FULL text output file FEPARAMS table Protocol Step Correct Dye Biases Correct Dye Biases Correct Dye Biases Correct Dye Biases Correct Dye Biases Correct Dye Biases Compute Ratios Compute Ratios Calculate Metrics Calculate Metrics Calculate Metrics Parameters DyeNorm_LOWESSSmoothFactor DyeNorm_LOWESSNumSteps DyeNorm_RankTolerance DyeNorm_VariableRank Tolerance DyeNorm_MaxRankedSize DyeNorm_IlsBGPopnOLOn Ratio_Version Ratio PegLogRatioValue OCMetrics UseSpikelns OCMetrics_minReplicatePopulation OCMetrics_differentialExpression PValue Type Options float integer float integer 1 True 0 False integer integer 1 True 0 False text float integer 1 True 0 False integer float Description Smoothing parameter Neighborhood size for LOWESS curve fitting Number of iterations in LOWESS The threshold to pick rank consistent features between 2 channels for measuring dye biases Allows the rank tolerance to vary with signal level to allow a fixed percentage of the data to be considered
134. llowable moment of inertia of the spot Factor from the statistics of the found feature and background that indicates if the spot is a spot Factor from the statistics of the found feature and background that indicates if the spot is a strong one Factor by which the individual spot background may vary from the running average of all the background means Type of Region of Interest If True the nominal spot diameter from the grid template is used as a starting point for final spot diameter computation If False the nominal diameter is obtained from the grid placement algorithm Pixel Outlier Rejection turned off Standard Deviation based Interquartile Range based Feature Extraction for CytoGenomics Reference Guide 75 Table 3 List of parameters and options contained within the FULL text output file FEPARAMS table Protocol Step Find Spots Find Spots Find Spots Find Spots Find Spots Find Spots Find Spots Find Spots Find Spots Find Spots 76 Parameters SpotAnalysis_StatBoundFeat SpotAnalysis StatBoundBG SpotAnalysis SpotStatsMethod SpotAnalysis CookiePercentage SpotAnalysis_ExclusionZone Percentage SpotAnalysis_EstimateLocalRadius SpotAnalysis_LocalBGRadius SpotAnalysis SignalMethod SpotAnalysis_ComputePixelSkew SpotAnalysis_PixelSkewCookiePct Type Options float float integer 1 2 float float integer 1 True 0 False float inte
135. lot of the log of the red background corrected signal versus the log of the green background corrected signal for non control inlier features The linearity or curvature of this plot can indicate the appropriateness of background method choices The plot should be linear The intersection of the red vertical and horizontal lines shows the location of the median signal The numbers along the edge of the lines represent the location of the median signal on the plot The values below the plot indicate the number of non control features that have a background corrected signal less than zero SNP probes are not included Red and Green Background Corrected Signals Non Control Inliers 100000 FS fal a A 100 1000 10000 100000 GBGSuUbSignal Background Subtracted Signal Features NonCtrl with BGSubSignals lt 0 0 Red 0 Green Figure 10 QC Report Plot of Background Corrected Signals Feature Extraction for CytoGenomics Reference Guide 33 34 Histogram of Signals Plot The purpose of this histogram is to show the level of signal and the shape of the signal distribution The histogram is a line plot of the number of points in the intensity bins vs the log of the processed signal SNP probes are not included signals Plot Number of Poms h Log of BG SubSignal A 0 a Histogram of Signals Features NonCtrl with BGSubSignal lt 0 4775 Green Figure 11 1 color QC Re
136. m Feature Extraction for CytoGenomics Reference Guide 35 36 RMS_Fit RMS_Resid Avg_Fit Figure 13 Foreground Surface Fit Red QC Report Foreground Surface Fit Feature Extraction for CytoGenomics Reference Guide Multiplicative Surface Fit See Step 16 Determine the error in the signal calculation on page 202 of this guide for more information about these calculations This is the root mean square RMS of the surface fit for the data The RMS X 100 is roughly the average deviation from flat on the microarray A multiplicative trend means that there are regions of the microarray that are brighter or dimmer than other regions This trend is an effect that multiplies signals that is a brighter signal is more affected in absolute signal counts than a dimmer signal SNP probes are not included in calculation of multiplicative detrending If the signal is improved through a multiplicative surface fit the RMS_Fit value appears as a fraction as in the figure below Multiplicative Surface Fit RMS_Fit Figure 14 QC Report Multiplicative Surface Fit What if multiplicative detrending does not work If the median CV for the Processed Signal of the non control probes is greater than the BGSub Signal median CV after multiplicative detrending Feature Extraction turns off multiplicative detrending The QC report shows an RMS_ Fit 0 0 if multiplicative detrending did not result in better data
137. m can also use a multiplicative detrend algorithm if selected or the default in the protocol to provide a surface fit to account for the dome effect that can happen when microarrays are processed Placing the error model calculation step before the significance calculation permits the result of the error model calculation to be used for the significance calculation surrogate calculation and multiplicative detrending steps Correct Dye Biases Since dye bias between the red and green channels is a common phenomenon in a dual color microarray platform this algorithm adjusts for the bias by multiplying the background subtracted signals with the appropriate dye normalization factors Both linear and non linear locally weighted normalization methods are available Surrogates are applied after the dye norm fit and before the dye normalization takes place This ensures that only real data contribute to the fit and also surrogate data is correctly dye normalized for both the Linear and Lowess options Because 1 color experiments use only the green channel they do not use this protocol step Surrogates exist and can be used for 1 color Feature Extraction for CytoGenomics Reference Guide Compute Ratios This algorithm determines if a feature is differentially expressed by calculating the log ratio of the red over green processed signals The processed signal is the dye normalized signal Because 1 color experiments use only the green
138. mScanPass Place Grid GridPlacement_Version Place Grid GridPlacement_ArrayFormat Place Grid GridPlacement_enableOriginXCal Feature Extraction for CytoGenomics Reference Guide Type Options text text integer 1 True 0 False text integer boolean 1 or 2 text integer integer 1 True 0 False Description Computer name on which Feature Extraction was run GUID of the scan file Indicates whether or not the extraction was an XDR extraction Name of the dye normalization list file Number of probes in the dye normalization list Indicates whether the grid is from a grid file For 5 micron scans indicates whether the scan mode was a Single 1 or double pass scan mode on the Agilent Scanner Version of the grid placement algorithm Choices for grid placement based on the format of the image Choices include Automatically Determine Single Density 11k 22k Double Density 44k 95k 185 5 and 10 uM 65 micron 5 and 10 uM 30 micron single pack 30 micron multi pack 244 5 and 10 uM 25k Third Party Indicates status of the Use the correlation method to obtain origin X of subgrids flag 73 Table 3 List of parameters and options contained within the FULL text output file FEPARAMS table Protocol Step Parameters Type Options Description Place Grid GridPlacement_enableUseCentralPack integer Indicates status of the Use central part of 1 True pack for slope and ske
139. mpleted In the case of one color ProcesssedSignal contains the Multiplicatively Detrended BackgroundSubtracted Signal if the detrending is selected and helps If the detrending does not help this column will contain the BackgroundSubtractedSignal Feature Extraction for CytoGenomics Reference Guide Table 11 Feature results contained in the MINIMAL output text file MINIMAL FEATURES table Features Green gProcessedSigError gNumPixOLHi gMedianSignal gPixNormlQR glsSaturated glsFeatNonUnifOL Features Red rProcessedSigError rNumPixOLHi rMedianSignal rPixNormlQR rlsSaturated rlsFeatNonUnifOL Types float integer float float boolean boolean Options 1 Saturated or 0 Not saturated g r lsFeatNonUnifO L 1 indicates Feature is a non uniformity outlier in g r Feature Extraction for CytoGenomics Reference Guide Description The universal or propagated error left after all the processing steps of Feature Extraction have been completed In the case of one color ProcessedSignalError has had the Error Model applied and will contain at least the larger of the universal UEM error or the propagated error lf multiplicative detrending is performed ProcessedSignalError contains the error propagated from detrending This is done by dividing the error by the normalized MultDetrendSignal Number of outlier pixels per feature with intensity gt upper threshold set
140. n Excellent Good Evaluate that is based on how the result compares to the given limit Feature Extraction for CytoGenomics Reference Guide value s Cases covered indicate the type of threshold along with the boundaries that are displayed in the QC Report value gt Upper limit gt Evaluate value gt Upper Warning limit and value lt Upper limit gt Good value gt Lower Warning limit and value lt Upper warning limit gt Excellent value gt Lower limit and value lt Lower Warning limit gt Good value lt Lower limit gt Evaluate Logic used Excellent Good Evaluate NA special case when vl v2 NA special case when wl v2 and v3 v4 gt vi or lt v4 NA special case when va v4 vi to v2 or v to v4 pea fana vl to v2 gt vl orug lt a v C gt v2 or vo to v4 vl to v2 or lt va Figure 36 QC Metrics evaluation tables and cases Feature Extraction for CytoGenomics Reference Guide Cases covered Boundaries 0 2 level metrics used in FEv10 5 Upper Good Evauate fr Good Evaluate 2 level metrics that may be used in FEv10 7 Excellent Good 4 Range Excellent Good 5 lower Excellent Good 6 Upper Excellent Evaluate Range Excellent Evaluate Excellent Evaluate 3 level metrics that may be used in FEv10 7 Excellent Good Evaluate Excellent Good Evaluate M Excellent Good Evaluate 3 level met
141. n at the second lowest concentration Agilent Spike In Concentration Response Statistic in the 1 color QC Report Log of low signal for the data Agilent Spike In Concentration Response Statistic in the 1 color QC Report Error in the log of low signal for the data Agilent Spike In Concentration Response Statistic in the 1 color QC Report Log of high signal for the data Agilent Spike In Concentration Response Statistic in the 1 color QC Report Log of low concentration in the linear range of curve fit Agilent Spike In Concentration Response Statistic in the 1 color QC Report Log of low signal in the linear range of curve fit 106 Feature Extraction for CytoGenomics Reference Guide Table 7 Stats results contained in the text output file STATS table continued Stats Green Channel Stats Red Channel eQCOneColorLinFitLogHigh Conc eQCOneColorLinFitLogHigh Signal eQCOneColorLinFitSlope eQCOneColorLinFitIntercept eQCOneColorLinFitRSO eQCOneColorSpikeDetection Limit gNonCtrl50PrentBGSubSig gNonCtrl50PrentBGSubSig gCtrleQC50PrcntBGSubSig rCtrleQC50PrcntBGSubSig Feature Extraction for CytoGenomics Reference Guide Type float float float float float float float float Description Agilent Spike In Concentration Response Statistic in the 1 color QC Report Log of high concentration in the linear range of curve fit Agilent Spike In Concentration Response Statistic in
142. n has been applied based upon the LOWESS curve Root mean square RMS of the fitted data points obtained from the Loess algorithm This gives an idea of the curvature of the surface fit Approximate residual from the surface fit Normalized area the fitted surface area divided by the projected area on the microarray also gives an idea of the curvature of the surface gradient Sum of the intensities of the surface area minus the offset The offset is calculated as the volume under the flat surface parallel to the glass slide passing through the minimum intensity point of the fitted surface This number total volume offset is normalized by the area of the microarray Describes the average intensity of the surface gradient 101 Table 7 Stats results contained in the text output file STATS table continued Stats Green Channel gNonCtriNumSatFeat gNonCtrl99PrentNetSig gNonCtrl50PrentNetSig gNonCtrl1 PrentNetSig gNonCtriMedPrentCVBGSub Sig gCtrleQCNumSatFeat gCtrleQC99PrcntNetSig gCtrleQC50PrentNetSig gCtrleQC1PrentNetSig geQCMedPrentCVBGSubSig geQCSig2BkgLow1 geQCSig2BkgLow2 gNegCtriNumInliers gNegCtrlAveNetSig 102 Stats Red Channel rNonCtriNumSatFeat rNonCtrl99PrentNetSig rNonCtrlb0PrentNetSig rNonCtrl1PrentNetSig rNonCtriMedPrentCVBGSubSig rCtrleQCNumSatFeat rCtrleQC99PrcntNetSig rCtrleQC50PrcntNetSig rCtrleQC1PrentNetSig reQCMedPrentCVBGSubSig
143. n Human 22K microarray image Human_22K_expression is included in the Example Images that Agilent provides on the Feature Extraction software installation CD 220 Feature Extraction for CytoGenomics Reference Guide Data from the FEPARAMS table BGSubtractor BGSubMethod BGSubtractor BackgroundCorrectionOn BGSubtractor SpatialDetrendOn 1 0 1 The BGSubMethod of 7 corresponds to No Background Subtraction method see Table 3 on page 71 of this guide Global Background Adjustment is turned Off Spatial Detrending is turned On Data from the STATS Table LowessDyeNormFactor is not shown in Feature Extraction result gLinearDyeNormFactor rLinearDyeNormFactor file This value can be back calculated using DyeNormSignal 15 881 4 14607 equation on page 245 Data from the FEATURES Table Results from Find And Measure Spots Algorithm FeatureNum gNumPix rNumPix gMeanSignal rMeanSignal gPixSDev rPixSDev 12519 62 62 3021 774 13502 52 187 8805 1102 547 Feature Extraction for CytoGenomics Reference Guide 221 Results from Correct Bkgd and Signal Biases Algorithm FeatureNum gSpatialDetrendSurfaceValue rSpatialDetrendSurfaceValue 12519 81 5464 72 2993 FeatureNum gBGUsed rBGUsed gBGSDUsed rBGSDUsed gBGSubSignal rBGSubSignal 12519 81 5464 72 2993 3 5514 5 34552 2940 23 13430 2 FeatureNum glsPosAndSignif rlsPosAndSignif glsWellAboveBG rlsWellAboveBG 12519 1 1 1 1 rBGUsed rSpatialDetrendSur face Value 72 2993 72 2993
144. n flag indicating if a feature is a NonUniformity Outlier or not A feature is non uniform if the pixel noise of feature exceeds a threshold established fora uniform feature 126 Feature Extraction for CytoGenomics Reference Guide Table 9 Feature results contained in the COMPACT output text file COMPACT FEATURES table continued Features Green glsBGNonUnifOL glsFeatPopnOL glsBGPopnOL IsManualFlag gBGSubSignal glsPosAndSignif Features Red rlsBGNonUnifOL rlsFeatPopnOL rlsBGPopnOL rBGSubSignal rlsPosAndSignif Types boolean boolean boolean boolean float boolean Options g r IsBGNonUnifOL indicates Local background is a non uniformity outlier in g r g r lsFeatPopnOL 1 indicates Feature is a population outlier in g r g r IsBGPopnOL 1 indicates local background is a population outlier in g r g r BGSubSignal g r MeanSignal g r BGUsed g r isPosAndSignif indicates Feature is positive and significant above background Feature Extraction for CytoGenomics Reference Guide Description The same concept as above but for background Boolean flag indicating if a feature is a Population Outlier or not Probes with replicate features on a microarray are examined using population statistics A feature Is a population outlier if its signal is less than a lower threshold or exceeds an upper threshold determined using a multiplier
145. n flag indicating if a feature is a NonUniformity Outlier or not A feature is non uniform if the pixel noise of feature exceeds a threshold established fora uniform feature The same concept as above but for background 119 Table 8 Feature results contained in the FULL output text file FULL FEATURES table continued Features Green glsFeatPopnOL glsBGPopnOL IsManualFlag gBGSubSignal gBGSubSigError BGSubSigCorrela tion Features Red rlsFeatPopnOL rlsBGPopnOL rBGSubSignal rBGSubSigError Types boolean boolean boolean float float float Options g r lsFeatPopnOL 1 indicates Feature is a population outlier in g r g r IsBGPopnOL 1 indicates local background is a population outlier in g r g r BGSubSignal g r MeanSignal g r BGUsed Description Boolean flag indicating if a feature is a Population Outlier or not Probes with replicate features on a microarray are examined using population statistics A feature is a population outlier if its signal is less than a lower threshold or exceeds an upper threshold determined using a multiplier 1 42 times the interquartile range i e IQR of the population The same concept as above but for background Boolean to flag features for downstream filtering in third party gene expression software Background subtracted signal To display the values used to calculate this variable using different back
146. n for CytoGenomics Reference Guide Excellent Good Evaluate Histogram of Signals Plot Red 5 11000 10000 9000 8000 7000 6000 5000 4000 3000 2000 1000 0 HHH h N EA EE ee Es 1 2 3 0 Q Number of Probes Q Streamlined CGH QC Report p1 7 Spatial Distribution of Significantly Up Regulated eae lwe Y Negalve and Down Regulated Kyaa i Tow at Naro ataa kandan Pake ba i d and Green Background Corrected Signals Non Control Features Positive and ne Inliers Negative Log Ratios on 8 page 38 8 Plot of rBG SubSignal Background Corrected Signals on page 33 100 1000 10000 100000 gBGSubSignal Features NonCtrl with BGSubSignals lt 0 26 Red 145 Green Figure 2 Streamlined CGH QC Report p2 Feature Extraction for CytoGenomics Reference Guide Page 2 of 2 23 OC reports with metric sets added When metric sets are associated to the protocols QC reports are generated with an additional set of evaluation metrics Depending on the microarray types some QC metric sets come with thresholds denoted by QCMT and some without thresholds denoted by QCM If thresholds are included in the metric set the evaluation tables in the QC report show metrics that are within threshold ranges or that have exceeded those ranges Agilent has determined which of the FE Stats are good metrics to follow the processing of our arrays Most of the metrics chosen will be useful
147. n have been completed In the case of one color ProcessedSignalError has had the Error Model applied and will contain at least the larger of the universal UEM error or the propagated error lf multiplicative detrending is performed ProcessedSignalError contains the error propagated from detrending This is done by dividing the error by the normalized MultDetrendSignal Number of outlier pixels per feature with intensity gt upper threshold set via the pixel outlier rejection method The number is computed independently in each channel These pixels are omitted from all subsequent calculations Number of outlier pixels per feature with intensity lt lower threshold set via the pixel outlier rejection method The number is computed independently in each channel These pixels are omitted from all subsequent calculations NOTE The pixel outlier method is the ONLY step that removes data in Feature Extraction Total number of pixels used to compute feature statistics i e total number of inlier pixels per spot same in both channels Raw mean signal of feature from inlier pixels in green and or red channel Raw median signal of feature from inlier pixels in green and or red channel 131 Table 10 Features Green gPixSDev gBGMeanSignal gBGMedianSignal gBGPixSDev glsSaturated glsLowPMT Scaled Up BGPixCorrelation glsFeatNonUnifOL glsBGNonUnifOL Features Red rPixSDev rBGMeanSignal r
148. nalyzed for rank consistency If red signal is plotted vs green signal and the slope of the rank consistent features is gt 1 then the pad value is assigned to the green channel If the slope is lt 1 the value is assigned to the red channel For instance if you set Adjust background globally to 50 and if the slope is 1 2 then a value of 50 is added to the green background subtracted signal of all features whereas a value of 50 1 2 60 is added to the red background subtracted signal of all features Feature Extraction for CytoGenomics Reference Guide 201 202 Conversely if you set Adjust background globally to 50 and if the slope is 0 5 then a value of 50 is added to the red background subtracted signal of all features whereas a value of 50 0 5 100 is added to the green background subtracted signal of all features Step 15 Calculate robust negative control statistics This algorithm repeats the population outlier algorithm but not on one sequence at a time rather on the distribution of all features that are classified as NegC or negative controls The algorithm calculates robust IQR statistics on features not designated as non uniform outliers population outliers or saturated UpperLimit 75th percentile Multiplier IQR LowerLimit 25th percentile Multiplier IQR The default value for this multiplier is 5 The algorithm then omits features that are outside the Upper and LowerLimits and calculates the ne
149. nd Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error 82 Parameters BGSubtractor SpatialDetrendOn BGSubtractor DetrendLowPassFilter BGSubtractor_DetrendLowPass Percentage BGSubtractor_DetrendLowPass Window BGSubtractor_DetrendLowPass Increment BGSubtractor_NegCtriSpreadCoeff BGSubtractor_NegCtriSpreadRobust On BGSubtractor_AdditiveDetrend FeatureSet Type Options integer 1 True 0 False integer 1 True 0 False integer integer integer float float integer List of parameters and options contained within the FULL text output file FEPARAMS table Description Spatial detrend turned on Spatial detrend turned off Low pass filter used Low pass filter not used Specifies percentage of features based on the lowest intensity probes in each window that will be used to fit the surface Specifies size of the square window by the number of rows and columns The specified percentage of low intensity features is selected from this window size The increment in number of features by which the above window is shifted horizontally and vertically on the microarray The number of multiples of the negative control spread that defines the signal range within which features are considered to be within the negative control range for
150. nd adjust see Table 20 on page 190 If significance is based on pixel statistics a Boolean flag of 1 indicates that the feature MeanSignal is greater than and significant compared to the background signal i e BGUsed If significance is based on the Additive Error of the Error Model a Boolean flag of 1 means that the feature MeanSignal is greater than and significant compared to the Additive Error A Boolean flag of 1 indicates that the feature BGSubSignal is well above background and passes the IsPosAndSignif test Set to true for a given feature if it is part of the filtered set used to detrend the background The feature may be in the set of locally weighted lowest x of features as defined by the DetrendLowPassPercentage may be a negative control feature or may be part of the set of features that are in the negative control range The feature set is defined by the detrend method selected Value of the smoothed surface at that feature calculated by the Spatial detrend algorithm Feature Extraction for CytoGenomics Reference Guide 167 Table 18 Algorithms Protocol Steps and the results they produce continued Protocol Step Compute Bkgd Bias and Error Compute Bkgd Bias and Error Correct Dye Biases Correct Dye Biases Compute Ratios Compute Ratios Compute Ratios 168 Results MultDetrendSignal SurrogateUsed DyeNormSignal LinearDyeNormFactor Table 3 on page 1 ProcessedSignal Process
151. ner Optimize Grid Fit This algorithm improves the grid fit on the entire microarray Leveraging from the Spot Finder algorithm this protocol step examines the spots in the four corners of the microarray and iteratively adjusting the grid for a better fit If the grid has been optimized by this protocol step the STATS table shows the stat GridHasBeenOptimized with boolean of 1 or a boolean of 0 if the grid has not been optimized Find Spots This algorithm locates the exact size and centroid of each spot on the scanned microarray Once the spot centroids have been located the CookieCutter algorithm or WholeSpot algorithm defines the feature for each spot The software then defines the local background for each spot based on the radius of a circle drawn around the spot Next the pixel outlier algorithm identifies outlier pixels in the feature and in the local background for each spot These pixels are then omitted from further calculations This is the only point where data is omitted Subsequent outlier analyses flag data but do not remove the data Inlier pixels within the cookie area represent a feature while the inlier pixels within the annulus around the feature after excluding the exclusion zone represent the local background The Feature Extraction program calculates the following Feature Extraction for CytoGenomics Reference Guide 161 162 values from these inlier pixels mean median standard deviation normalize
152. ng negative controls is not possible For CGH microarrays the error model choice is to make this term and m3 zero and use only m1 because there are a variety of sequences used for the negative controls GE1 GE2 and miRNA 0 CGH and ChIP 0 non Agilent 4 Multiplier for the third term in the equation and is the width of the distribution of signals used in the background spatial detrending set after the background surface has been subtracted out When the background detrending set includes a group of features well distributed across the microarray with a variety of sequences the width of the distribution of the signals of these features after background subtraction is a very good estimate of the uncertainty of the dim signals or the additive error GE1 GE2 and miRNA 1 CGH and ChIP 0 non Agilent 0 Feature Extraction for CytoGenomics Reference Guide Step 17 Calculate the significance of feature intensity relative to background IsPosAndSignif The significance of the feature intensity compared to the background intensity local or global is calculated using two different significance tests one using pixel statistics for both the feature and the background values and the other using the additive error from the Error Model calculation for the background value Significance based on pixel statistics This method to determine significance uses the 2 sided Student s t test with mean signal for the feature and the b
153. ns on the linear curve with the expected log signals for the same concentrations on the sigmoidal curve For the high end of the linear range the difference is 15 36 For the low end of the linear range the difference is 16 75 Feature Extraction for CytoGenomics Reference Guide OC Report Results in the FEPARAMS and Stats Tables See Parameters options The FEPARAMS table contains most of the QC header FEPARAMS on page 71 and information The Stats table output contains all the metrics Statistical results STATS on shown on the QC Reports These QC stats let you make page 98 of this guide for tracking charts of individual metrics that you may want to descriptions of the parameters and follow over time To separate out the FEPARAMS and Stats statistics listed in the tables tables from each other and the FEATURES table see the Agilent Feature Extraction for CytoGenomics User Guide Feature Extraction for CytoGenomics Reference Guide 59 QC Metric Set Results The figures below show the metric names and default thresholds for the QC metric set results that appear in the Evaluation Tables for each of the QC metric sets available for Feature Extraction for CytoGenomics You can display the QC Metric Set For details on the logic used for evaluating metrics see Properties by double clicking on a Metric Evaluation Logic on page 66 QC metric set in the QC Metric Set Done Note that SNP probes are not used
154. o per each feature e g gene between the red and green channels The p value is a measure of the confidence viewed as a probability that the feature is not differentially expressed For example if the p value is less than 0 01 we can say with a 99 confidence level that the gene is differentially Feature Extraction for CytoGenomics Reference Guide 215 For more details on calculations with the Universal Error Model see the confidential Agilent technical paper on error modeling 216 expressed In other words there would be a 1 random chance of getting this low of a p value with a gene that is actually not differentially expressed p value ie Erfe EEEX 31 where Erf x Apea 32 dp Erf is the error function of the expression y as given by the above equation It is twice the integral of the Gaussian distribution with mean 0 and variance 1 2 Erfc is the complementary error function as defined by the above equation udev is the deviation of LogRatio from 0 LogRatio xdev 2 _ LogRatioError 33 Equation 22 is analogous to a signal to noise metric If the Universal Error Model is used then xdev is computed from six sources e ProcessedSignals red and green channels e Multiplicative error factors red and green e Additive error factors red and green The terms xdev multiplicative error and additive error come from the Universal Error Model as dev
155. og ratio for all inlier non control probe sets with a minimum number of replicates Feature Extraction for CytoGenomics Reference Guide 103 Table 7 Stats results contained in the text output file STATS table continued Stats Green Channel eQCAbsAveLogRatio eQCSDevLogRatio eQCSNRLogRatio AddErrorEstimateGreen AddErrorEstimateRed TotalNumFeatures NonCtriNumUpReg NonCtrINumDownReg eQCObsVsExpLRSlope eQCObsVsExpLRintercept Stats Red Channel Type float float float float float integer integer integer float float Description This result is from a two step calculation Step 1 for each probe calculates the absolute average log ratio of all inlier spikein features with minimum number of replicates Step 2 calculates the average of all absolute average log ratios calculated in step 1 Average standard deviation of log ratios of all inlier spike in probe sets with a minimum number of replicates Average signal to noise value of log ratios of all inlier spike in probe sets with a minimum number of replicates The additive error estimated for the microarray in the green channel The additive error estimated for the microarray in the red channel Total number of features that show up in output file Number of up regulated non control probes Number of down regulated non control probes For 2 color QC report Slope of the linear regression fit of the plot of th
156. on on TIFF files and formats fhe Agilent Technologies 141 How Agilent output file formats are used by databases Pattern files should be loaded to the database via FTP if possible to ensure that the pattern element name attribute is used to name the pattern 142 Data analysis programs must match up information about the layout and annotation of the microarray features with the profile result files for each microarray within their databases Agilent provides this design information for its microarrays in a variety of file formats including GAL and MAGE ML These files describe the gene probes and their number and spacing on the microarray Profile result files contain the signal and error information for each of the hybridized gene probes on the microarray Both pattern files and profile result files contain information that can be formatted in several ways tab delimited text format or an XML format MAGE ML Agilent only supports GEML2 Pattern files and MAGE ML profiles for use with Rosetta Resolver The pattern name in Rosetta Resolver should match the profile pattern name embedded in the profile data so that the data can be correctly associated To do this use the pattern autoimport function in Rosetta Resolver or correctly specify the pattern name when manually importing the pattern The Agilent pattern name in most cases is Agilent xxxxxx where the XxXxxxx 1S the AMADID number of the microarray For transfer of
157. onUnifOL TotalNumberOfReplicated Genes Stats Red Channel Type rOutlierFlagger_Auto_BgndC float Term float float rXDRLowPMTSlope rXDRLowPMT Intercept integer integer integer Feature Extraction for CytoGenomics Reference Guide Description Applies to background specifies variance due to background noise of the scanner slide glass and other signal independent sources automatically calculated when OLAutoCompute is turned on Confidence Interval for the feature Confidence Interval for the background The slope that is multiplied by the original low intensity Mean Signal to get the XDR mean signal Used in the linear equation relating the Mean or Median Signal in the low intensity scan to the scaled intensity used in the combined XDR output The intercept that is added to the Slope LowIntensityMeanSignal to get the XDR Mean Signal Used in the linear equation relating the Mean or Median Signal in the low intensity scan to the scaled intensity used in the combined XDR output Indicates that the automatic image processing was flagged as needing evaluation Number of genes that do not have any replicate features on the array where both color channels are not Feature Non Uniform outliers If multiple probes address the same gene this value actually states the number of probes that have no non uniform replicates Number of genes that have replicate features on the array 109 Table 7 Stats results conta
158. opulation outlier in either color and the Report Population Outliers as Failed in MAGE ML file option is set to True Bit 23 is set if the probe is low specificity e g when the deletion control is greater than or equal to the feature Feature Extraction for CytoGenomics Reference Guide 157 TIFF Results See the Agilent Feature Extraction for CytoGenomics User Guide for more information on the File Info dialog box TIFF Tag 37701 TIFF Tag 37702 158 You can transfer the original TIFF file or a JPEG file to Rosetta Resolver or a third party program The shape file Shp created during Feature Extraction cannot be displayed by any program other than Agilent Feature Extraction software TIFF file format options Feature Extraction supports the TIFF file format All file information for each file is listed in the File Info dialog box The TIFF file is compliant with Adobe version 6 0 file format The complete specification is available from the following URL http partners adobe com asn developer PDFS TN TIFF6 pdf There are two sets of custom TIFF tags in the Agilent file format Genetic Analysis Technology Consortium GATC TIFF Tags Agilent Technologies is not a member of GATC or otherwise connected to this organization and makes no internal use of these tags They are included for the convenience of customers who use software that requires them Custom TIFF Tags Agilent Technologies uses its own custom TIFF tags
159. or CytoGenomics Reference Guide Table of Values for Concentration Response Plot 1 color only This table presents the values for the log signal vs log concentration plot shown in Figure 28 Agilent Spike In Concentration Response Statistics Linear Range Statistics Low Signal High Signal Low Relative Concentration High Relative Concentration Slope R Value Signal Detection Limit Statistics Saturation Point Low Threshold Low Threshold Error Spike In Detection Limit Figure 29 1 color QC Report Agilent Spike In Concentration Response Statistics Detection of missing spike ins This section describes how Feature Extraction deals with missing spike ins Case 1 If the array has a Grid Template with NO SpikeIns in the design e If standard protocol is run then Feature Extraction will give a Warning in the Summary Report that there are no SpikelIn probes e If protocol has SpikeIn Used set to False then the QC metric table in the QC Report will show for values and black font instead of red green or blue fonts indicating no evaluation has been done by Feature Extraction Specialized SpikeIn plots amp tables will be omitted from the report Feature Extraction for CytoGenomics Reference Guide 53 Case 2 If the array has a Grid Template WITH SpikelIns in the design but the user adds no Spikelns to hyb e If standard protocol is run the results will either be wrong values or listed as
160. or most conservative Most Conservative 18 Feature Extraction for CytoGenomics Reference Guide Table 1 Default settings for the preloaded CGH protocols Protocol Step Correct Dye Biases Compute Ratios Calculate Metrics Generate Results Parameter MultErrorGreen MultErrorRed Auto Estimate Add Error Red Auto Estimate Add Error Green Use Surrogates Use Dye Norm List Dye Normalization Probe Selection Method Rank Tolerance Variable Rank Tolerance Signal Characteristics Normalization Correction Method Max Number Ranked Probes Omit Background Population Outliers Allow Positive and Negative Controls Peg Log Ratio Value Grid Test Format Spikein Target Used Min Population for Replicate Stats PValue for Differential Expression Percentile Value Type of QC Report Generate Single Text File JPEG Down Sample Factor Default Setting Value v10 10 0 1000 0 1000 True True True Automatically Determine Use Rank Consistent Probes 0 050 False OnlyPositiveAndSignificantSignals Linear 1 False False 4 00 Automatically Determine Recognized formats 60 and 30 micron feature size third party False 3 0 010000 75 00 Streamlined CGH True 4 Feature Extraction for CytoGenomics Reference Guide 19 20 Feature Extraction for CytoGenomics Reference Guide Agilent CytoGenomics 3 0 Agilent Feature Extraction for CytoGenomics Reference Guide 2 OC Report Results QC Repor
161. otice in future editions Further to the max imum extent permitted by applicable law Agilent disclaims all warranties either express or implied with regard to this manual and any information contained herein including but not limited to the implied warranties of merchantability and fitness for a par ticular purpose Agilent shall not be liable for errors or for incidental or consequential damages in connec tion with the furnishing use or per formance of this document or of any information contained herein Should Agilent and the user have a separate written agreement with warranty terms covering the material in this document that conflict with these terms the warranty terms in the sep arate agreement shall control Technology Licenses The hardware and or software described in this document are furnished under a license and may be used or copied only in accor dance with the terms of such license Restricted Rights Legend U S Government Restricted Rights Soft ware and technical data rights granted to the federal government include only those rights customarily provided to end user cus tomers Agilent provides this customary commercial license in Software and techni cal data pursuant to FAR 12 211 Technical Data and 12 212 Computer Software and for the Department of Defense DFARS 252 227 7015 Technical Data Commercial Items and DFARS 227 7202 3 Rights in Commercial Computer Software or Com puter Softw
162. play variables used in the t test see lable 20 on page 190 pValue from t test of significance between g r Mean signal and g r background selected by user Number of local background regions or features used to calculate the background used for background subtraction on this feature Boolean flag indicating if a feature is WellAbove Background or not feature passes g r lsPosAndSignif and additionally the g r BGSubSignal is greater than 2 6 g r BG_SD You can change the multiplier 2 6 Background used to subtract from the MeanSignal variable also used in t test To display the values used to calculate this variable using different background signals and settings of spatial detrend and global background adjust see Table 20 on page 190 Standard deviation of background used in g r channel variable also used in t test and surrogate algorithms To display the values used to calculate this variable using different background signals and settings of spatial detrend and global background adjust see Table 20 on page 190 A boolean flag which indicates if a feature is used to measure dye bias 121 Table 8 Feature results contained in the FULL output text file FULL FEATURES table continued Features Green gDyeNormSignal gDyeNormError DyeNormCorrelation ErrorModel xDev gSpatialDetrendlsIn FilteredSet gSpatialDetrend SurfaceValue glsLowEnoughAdd Detrend SpotExtentX SpotExtentY 122
163. port Histogram of Signals Plot Feature Extraction for CytoGenomics Reference Guide Local Background Inliers With these numbers you can see the mean signal distribution for the local background regions BGMeanSignal after outliers have been removed This information can help you detect hybridization wash artifacts and can be a component of noise in the low signal range SNP probes are included Local Bkg inliers Red 22105 49 77 0 93 Figure 12 QC Report Local Background Inliers Foreground Surface Fit See Step 13 Perform background Spatial Detrend attempts to account for low signal spatial detrending to fit a background that is present on the feature foreground and surface on page 192 of this guide varies across the microarray SNP probes are not included for more information about these e A high RMS_Fit number can indicate gradients in the low calculations signal range before detrending e RMS_Resid indicates residual noise after detrending e AvgFit indicates how much signal is in the foreground A higher AvgF it number indicates a larger amount of signal was detected by the detrend algorithm and removed This value may include the scanner offset unless a background method has been used before detrending The value may not include higher frequency background signals These higher frequency background signals are best removed by using the Local Background Method before the detrending algorith
164. r than the median of 97 and half below the median of 97 The median or 50th percentile represents the middle of the ranked values of the distribution of signals Another indicator of signal range for the microarray is the number of features that are saturated in the scanned image i e NumSat Net Signal Statistics Agilent SpikeIns Red Saturated Features 99 of Sig Distrib 50 of Sig Distrib 1 of Sig Distrib 160 Non Control probes Red Saturated Features 16 99 of Sig Distrib 50 of Sig Distrib 1 of Sig Distrib Figure 8 QC Report Net Signal Statistics Feature Extraction for CytoGenomics Reference Guide 31 32 Negative Control Stats The Negative Control Stats table includes the average and standard deviation of the net signals mean signal minus scanner offset and the background subtracted signals for both the red and green channels in the negative controls These statistics filter out saturated and feature non uniform and population outliers and give a rough estimate of the background noise on the microarray SNP probes are not included in these statistics Negative Control Stats Average Net Signals StdDey Net Signals Average BG Sub Signal StdDev BG Sub Signal BG Noise Red Green 19 60 mar 0 33 4 96 Figure 9 QC Report Negative Control Stats Feature Extraction for CytoGenomics Reference Guide Plot of Background Corrected Signals Figure 10 is a p
165. rger this value the more differential expression is present Array Uniformity LogRatios Non Control Agilent SpikeIns AbsAvgLogRatio 0 26 0 48 AverageS N 3 86 43 07 Figure 20 QC Report Array Uniformity LogRatios Feature Extraction for CytoGenomics Reference Guide Sensitivity These values represent the NetSignal to background BGUsed ScannerOffset ratio of the two spike in probes with the lowest background subtracted signal Their purpose is to characterize the sensitivity of detecting a low signal relative to the background Sensitivity Agilent SpikeIns Ratio of Signal to Background for 2 dimmest probes E1A_r60_n11 E1A_r60_a97 g g r 15 0 Puck Figure 21 QC Report Sensitivity Agilent Spikelns Ratio of Signal to Background for 2 dimmest probes Feature Extraction for CytoGenomics Reference Guide 45 Reproducibility Plots Reproducibility plot for 2 color gene expression spike in probes Signal replicate statistics are calculated for spike in probes if three criteria are met e They are present on the microarray e The protocol indicates that labeled target to these spike in probes has been added in the hybridization QCMetrics_UseSpikelIns is True e There are a minimum number of inlier features for calculations QCMetrics_minReplicatePopulation As described above for non control probes CV s are calculated for inliers for both red and green background corrected signals
166. rics that are asymmetric supported but not normally used FEv10 7 Range Excellent Good Evaluate Excellent Good Evaluate 14 Excellent Good Evaluate 15 Excellent Good Evaluate 16 Excellent Good Evaluate Excellent Good Evaluate 18 Range Range Range Range Range 67 Feature Extraction for CytoGenomics Reference Guide FEPARAMS table STATS table FEATURES table Agilent CytoGenomics 3 0 Agilent Feature Extraction for CytoGenomics Reference Guide 3 Text File Parameters and Results Parameters options FEPARAMS 71 FULL FEPARAMS Table 71 COMPACT FEPARAMS Table 89 QC FEPARAMS Table 92 MINIMAL FEPARAMS Table 95 Statistical results STATS 98 STATS Table ALL text output types 98 Feature results FEATURES 114 FULL Features Table 114 COMPACT Features Table 124 QC Features Table 129 MINIMAL Features Table 135 Other text result file annotations 139 Feature Extraction produces a tab delimited text file that contains three tables of input parameters and output results These tables are FEPARAMS STATS and FEATURES These three tables list all the possible parameters statistics and feature results that can be generated in the text output file Contains input parameters and options used to run Feature Extraction Gives results derived from statistical calculations that apply to all features on the microarray Displays results for each feature in over 90 output columns such as gene name log ratio process
167. ription Type SOT glsBGNonUnifOL rlsBGNonUnifOL g r IsBGNonUnifOL 1 The same concept as above but for indicates Local background background is a non uniformity outlier in g r SOT glsFeatPopnOL rlsFeatPopnOL g r lsFeatPopnOL 1 Boolean flag indicating if a feature is indicates Feature is a a Population Outlier or not Probes population outlier in g r with replicate features on a microarray are examined using population statistics A feature is a population outlier if its signal is less than a lower threshold or exceeds an upper threshold determined using a multiplier 1 42 times the interquartile range i e IQR of the population SOT glsBGPopnOL rlsBGPopnOL g r IsBGPopnOL 1 The same concept as above but for indicates local background background is a population outlier in g r SOT gBGSubSignal rBGSubSignal gBGSubSignal Background subtracted signal gMeanSignal gBGUsed To display the values used to calculate this variable using different background signals and settings of spatial detrend and global background adjust see Table 20 on page 190 SOT IsManualFlag Boolean flag that describes if the feature centroid was manually adjusted 154 Feature Extraction for CytoGenomics Reference Guide Table 16 Feature results Compact contained in the MAGE ML FEATURES table Quant Features Green Features Red Type SOT glsPosAndSignif rlsPosAndSignif SQT glsWellAboveBG rlsWellAboveBG SQT Specialized Quant
168. rm outliers in either channel Stat name AnyColorPrentBGNonUnifOL Threshold_Max 2 How broad is the distribution of NegControl net signals Stat name Max gNegCtrlSDevNetSig rNegCtr1SDevNetSig Threshold_Max 100 What is the median CV of BGSubSignal of the NonControl replicated sequences Stat names Max gNegCtr1MedPrcentCVBGSubSig rNegCtrl1MedPrcentCVBGSubSig or just the green stat fora 1 color application Threshold_Max 50 What is the difference between feature centers found by the sridding algorithm vs the spot finding algorithm Stat names Max CentroidDiffx CentroidDiffY Threshold_Max 10 Feature Extraction for CytoGenomics Reference Guide Optional Test6 How many features along the edge of the microarray are flagged as non uniform outliers in either channel This test is used only if one of these two metrics is unavailable e No replicated features are present to calculate the NonCtrlMedPrentCVBGSubSig metric e Or no NegControls are present to calculate the StdDev Stat name MaxNonUnifEdges Threshold_Max 10 Feature Extraction for CytoGenomics Reference Guide 219 Example calculations for feature 12519 of Agilent Human 22K image Feature 12519 Found Gene name DRO4 Intensity Red 13502 5166 Green 3021 7742 Red Green Log Ratio 0 0309 Figure 51 Visual results of feature number 12519 from Shapes file shp of Human_22K_expression microarray image The 2 color gene expressio
169. rmost feature to the edge of a circle that approximately surrounds the fourth closest set of nearest neighbors or n 4 as shown in Equation 2 The set of eight nearest neighbors closest to the feature of interest is defined as n 1 as shown in Equation 3 Feature Extraction for CytoGenomics Reference Guide 179 Figure 43 Example of the radius for the first closest set of nearest neighbors or n 1 eight nearest neighbors The value of the maximum radius also depends on the scan resolution and interspot spacing in the TIFF and grid template or file shown in the equation below Max radius CEILING Scan_resolution x 4 7 N Interspotspacing x Interspotspacing 2 where CEILING rounds the calculated value up to the next higher integer e g CEILING 38 2 4 Anyradius The value of any radius between the minimum and maximum that circumscribes a circle surrounding the nth closest set of nearest neighbors from the central spot can be approximated as Radius_n Scan_resolution x n 6 Interspotspacing x Interspotspacing yy 3 where n 1 2 3 or 4 Figure 44 shows the set of nearest neighbors where n 2 180 Feature Extraction for CytoGenomics Reference Guide 24 nearest neighbors n 2 Figure 44 Example of the radius for the second closest set of nearest neighbors or n 2 Step 6 Reject outliers The calculation to determine the boundaries for rejection of the outlier pixels is defined below in the equ
170. rotocol Name text Name of protocol used Protocol date text Date the protocol was last modified Scan_date text Date the image was scanned Scan_ScannerName text Serial number of the scanner used Scan_NumChannels integer Number of channels in the scan image Scan_MicronsPerPixelX float Number of microns per pixel in the X axis of the scan image Scan_MicronsPerPixelY float Number of microns per pixel in the Y axis of the scan image Scan_OriginalGUID text The global unique identifier for the scan image Grid_Name text Grid template name or grid file name Grid_Date integer Date the grid template or grid file was created Grid_NumSubGridRows integer Number of subgrid columns Grid_NumSubGridCols integer Number of subgrid columns Grid_NumRows integer Number of spots per row of each subgrid Grid_NumCols integer Number of spots per column of each subgrid Feature Extraction for CytoGenomics Reference Guide 71 Table 3 List of parameters and options contained within the FULL text output file FEPARAMS table Protocol Step Parameters Grid_RowSpacing Grid_ColSpacing Grid_OffsetX Grid_OffsetY Grid_NomSpotWidth Grid_NomSpotHeight Grid_GenomicBuild FeatureExtractor Barcode FeatureExtractor_ Sample FeatureExtractor_ScanFileName FeatureExtractor_ArrayName FeatureExtractor_DesignFileName FeatureExtractor_PrintingFileName FeatureExtractor_PatternName FeatureExtractor_Extractionlime FeatureExtractor_ UserName T
171. s Diameter of the spot Y axis Feature Extraction for CytoGenomics Reference Guide Table 8 Feature results contained in the FULL output text file FULL FEATURES table continued Features Green gNetSignal gMultDetrendSignal gProcessed Background gProcessedBkng Error IsUsedBGAdjust glnterpolatedNeg CtrlSub glsInNegCtrlRange glsUsedInMD Features Red rNetSignal rMultDetrendSignal rProcessed Background rProcessedBkng Error rinterpolatedNeg CtrlSub rlsInNegCtriRange rlsUsedInMD Types float float float float boolean float boolean boolean Options 1 Feature used 0 Feature not used Description MeanSignal minus DarkOffset A surface is fitted through the log of the background subtracted signal to look for multiplicative gradients A normalized version of that surface interpolated at each point of the microarray Is stored in MultDetrendSignal The surface is normalized by dividing each point by the overall average of the surface That average Is stored in MultDetrendSurfaceAverage as a statistic 1 color only Indicates the Background signal that was selected to be used Mean or Median Indicates the Background error that was selected to be used PixSD or NormlQR A Boolean used to flag features used for computation of global BG offset Value at the polynomial fit of the negative controls Set to true for a given feature if its signal intensit
172. sed in the calculation of AdditiveError for the CGH error model To provide an estimate of the error in the background subtracted signal calculation the error model is now calculated after background subtraction The 1 color error model has been changed to exactly mimic the 2 color error model To determine if the feature intensity is significant compared to the background intensity two kinds of tests are available t test and WellAboveBG test Both of these tests depend upon an estimation of background error The default protocol for older Agilent protocols still uses pixel statistics of local background regions to estimate background error in the 2 sided t test Newer Agilent protocols use an improved estimation of background error Feature Extraction for CytoGenomics Reference Guide 163 164 the additive error calculated from the Agilent error model You can choose between these two background error estimations in the protocol parameter field Significance for IsPosAndSignif and IsWellAboveBG The WellAboveSDMulti confidence test is used to determine if the feature background subtracted signal is well above its background error Surrogates are calculated here and depend on the significance model used Given the standard t test the surrogates are calculated exactly as before Given the new significance test based upon additive error the surrogate value is determined by the additive error and the p value The progra
173. sedSignal C for Green Figure 24 miRNA QC Report Reproducibility CV for Replicated Probes Feature Extraction for CytoGenomics Reference Guide Spike in Signal Statistics 2 color gene expression spike in signal statistics These signal statistics and S N values for spike ins indicate accuracy and reproducibility of the signals of the microarray probes The table shows the expected signal of the spike in probe the observed average signal the SD of the observed signal and the S N of the observed signal Agilent SpikeIns Signal Statistics Probe Name Exp Obs SD E1A_r60_n9 1 00 E1A_r60_a107 0 48 E1A_r60_a135 0 48 E1A_r60_n11 0 48 E1A4_r60_1 0 00 E1A_r60_a20 0 00 E1A_r60_3 0 48 E1A_r60_a104 0 48 E1A_r60_a97 0 48 E1A_r60_a22 Figure 25 2 color QC Report Agilent Spikelns Signal Statistics Feature Extraction for CytoGenomics Reference Guide 50 1 color gene expression spike in signal statistics For each sequence of spike ins this table shows the Probe Name the median Processed Signal median of LogProcessedSignal CV SD_ProcessedSignals Avg_ProcessedSignals and StdDev of LogProcessedSignals Agilent SpikeIns Signal Statistics Median Log Probe Name Relative i CV StdDev Conc E1A_r60_3 56 49 E1A_r60_a104 0 98 17 59 E1A_r60_a107 3 1 67 9 72 E1A_r60_a135 270 3 93 E1A_r60_a20 3 06 5 47 E1A_r60_a22 3 63 6 56 E1A_r60_a97 4 17 6 17
174. t float text 1 or2 text integer integer integer integer integer float float float Description Name of protocol used Date the protocol was last modified Agilent scanner serial number used Number of channels in the scan image Date the image was scanned Number of microns per pixel in the X axis of the scan image Number of microns per pixel in the Y axis of the scan image The global unique identifier for the scan image For 5 micron scans indicates whether the scan mode was a single 1 or double pass scan mode on the Agilent Scanner Grid template name or grid file name Date the grid template or grid file was created Number of subgrid columns Number of subgrid columns Number of spots per row of each subgrid Number of spots per column of each subgrid Space between rows on the grid Space between column on the grid In a dense pack array the offset in the X direction Feature Extraction for CytoGenomics Reference Guide 89 Table 4 List of parameters and options contained within the COMPACT text output file FEPARAMS table Protocol Step 90 Parameters Grid_OffsetY Grid_NomSpotWidth Grid_NomSpotHeight Grid_GenomicBuild FeatureExtractor_Barcode FeatureExtractor_ Sample FeatureExtractor ScanFileName FeatureExtractor_ArrayName FeatureExtractor_ScanFileGUID FeatureExtractor_DesignFileName FeatureExtractor_Extractionlime FeatureExtractor UserName F
175. t background signals and settings of spatial detrend and global background adjust see Table 20 on page 190 Boolean flag established via a 2 sided t test indicates if the mean signal of a feature is greater than the corresponding background selected by user and if this difference is significant To display variables used in the t test see lable 20 on page 190 Boolean flag indicating if a feature is WellAbove Background or not feature passes g r lsPosAndSignif and additionally the g r BGSubSignal is greater than 2 6 g r BG_SD You can change the multiplier 2 6 133 Table 10 Feature results contained in the QC output text file QC FEATURES table Features Green Features Red Types Options Description SpotExtentX float Diameter of the spot X axis gBGMeanSignal rBGMeanSignal float Mean local background signal local to corresponding feature computed per channel inlier pixels 134 Feature Extraction for CytoGenomics Reference Guide MINIMAL Features Table Table 11 Feature results contained in the MINIMAL output text file MINIMAL FEATURES table Features Green Features Red Types Options Description FeatureNum integer Feature number Row integer Feature location row Col integer Feature location column Control Type integer Feature control type See XML Control Type output on page 156 for definitions 0 Control type none 1 Positive control 1 Negative control 15000 SNP 20000 Not prob
176. t t where t is the threshold percentile then feature passes the rank consistency filter between the red and green channels and falls within the central tendency of the data Note 7 is a user defined parameter in the Feature Extraction program Feature Extraction for CytoGenomics Reference Guide 211 The LinearDyeNormFactor red and green channels values are listed in the STATS table 212 Using Rank Consistent List of Normalization Genes This method uses the rank consistent normalization genes from the list These genes follow the criteria described above Step 22 Calculate the normalization factor LinearDyeNormFactor The linear dye normalization method assumes that dye bias is not intensity dependent and therefore takes a global approach to dye normalization A linear dye normalization factor is computed per channel by setting the geometric mean of signal intensity of the normalization features equal to 1000 1000 1S oe 10 7 LinearDyeNormFactor 26 where X is the background subtracted signal of a feature i e BGSubSignal where n is the number of features used for normalization i e features with IsNormalization 1 LOWESSDyeNormFactor The LOWESS dye normalization method assumes that dye bias may be intensity dependent and therefore takes a local approach to dye normalization The LOWESS dye normalization factor is calculated by fitting the locally weighted linear regression curve to the chosen norm
177. ta for bright features less affected by saturation The Feature Extraction program uses a signal level of 20 000 as the cut off between the two scans If the NetSignal of the high intensity scan is greater than 20 000 counts then the data from the low intensity scan is used The low intensity scan is scanned with a lower PMT gain than the high intensity scan say 10 versus 100 So to combine the data the signals from the low intensity scan must be increased to match those from the high intensity scans To determine the factor by which the low intensity signal should be scaled the algorithm uses features that have signals in an overlap range where both the high and low intensity scans provide very stable data This range is Net Signals in the high intensity scan greater than 300 counts and less than 20 000 counts Using data in this range the Feature Extraction program generates a linear fit with a slope and an intercept that transforms the low intensity mean signals into the same range as high intensity scans The final scaled signal for the XDR extraction is MeanSignal low intensity scan slope intercept The linear fit constants determined in this step are included in the stats table For signals over 20 000 counts in the high intensity scan therefore the low intensity scan signals can extend to nearly 1 2 million counts If the low intensity scan has a spot centroid too far from the high intensity centroid grea
178. teger Type of OC report to generate 0 Gene Expression 1 CGH_ChIP 2 miRNA 4 Streamlined CGH DyeNorm_NormFilename text Name of the dye normalization list file DyeNorm_NormNumProbes integer Number of probes in the dye normalization list Grid_IsGridFile boolean Feature Extraction for CytoGenomics Reference Guide 91 QC FEPARAMS Table Table 5 List of parameters and options contained within the QC text output file FEPARAMS table Protocol Step 92 Parameters Protocol Name Protocol date Scan_ScannerName Scan_NumChannels Scan_date Scan_MicronsPerPixelX Scan_MicronsPerPixelY Scan_OriginalGUID Scan_NumScanPass Grid_Name Grid_Date Grid_NumSubGridRows Grid_NumSubGridCols Grid_NumRows Grid_NumCols Grid_RowSpacing Grid_ColSpacing Grid_OffsetX Type Options text text text integer text float float text 1 or2 text integer integer integer integer integer float float float Description Name of protocol used Date the protocol was last modified Agilent scanner serial number used Number of channels in the scan image Date the image was scanned Number of microns per pixel in the X axis of the scan image Number of microns per pixel in the Y axis of the scan image The global unique identifier for the scan image For 5 micron scans indicates whether the scan mode was a single 1 or double pass scan mode on the Agilent Scanner Grid template name or grid fil
179. tensity gt 300 100 to 300 100 rRepro Oto 0 10 0 10 to 0 20 0 or gt 0 20 r_BGNoise lt 10 10 to 20 gt 20 rSignal2Noise gt 100 50 to 100 lt 50 r Signallntensity gt 300 100 te 300 100 RestrictionControl 0 80 to 1 lt 0 80 or gt 1 LogRatiolmbalance 0 26 to 0 26 0 75 to 0 26 or 00 26 to 0 75 lt 0 75 or 0 75 Figure 31 QC Metrics for CytoCGH_QCMT_2x_Mar14 metric set Feature Extraction for CytoGenomics Reference Guide CytoCGH OCMT 4x Mar14 zt OT rene L Prope Metric Set Info Created On Type Description Removable 20 Mar 2014 11 01 Agilent False Metric Name IsGood6rid AnyColorPrentFeatNonU DerivativeLR_Spread gRepro g_BGNotse g_Signal2Noise g_Signallntensity rRepro r_BGNoise rSignal2Noise r Signallntensity RestrictionControl LogRatiolmbalance Figure 32 Excellent gt 1 lt 1 0 20 0 to 010 lt 10 100 gt 400 0 to 010 lt 10 gt 100 gt 400 0 26 to 0 26 0 75 to 0 26 or 0 26 to 0 75 eee EA ROEN E pe dil gach R A j eet ee Se Be eet TRS E yperties Cyto OH OCMIT LEE F LL p il Good NA l to5 0 20 to 0 30 0 10 to 0 20 10 to 20 50 to 100 200 to 400 0 10 to 0 20 10 to 20 50 to 100 200 to 400 0 80 tol Ewaluate lt 0 or 0 20 gt 20 lt 50 lt 200 lt 0 or gt 0 20 gt 20 lt 50 lt 200 lt 0 80 of gt 1 lt 0 75 or gt 0 75 QC Metrics for CytoCGH OQCMT _4x_Mar14 metric set Feature Extrac
180. ter than 2 pixels the algorithm does not make a substitution Feature Extraction for CytoGenomics Reference Guide Troubleshooting the XDR extraction The XDR algorithm provides warnings in the project summary report to indicate an issue with the XDR extraction process e No XDR signal substitution for color red green This message appears if there are no features for which the low intensity data are substituted This could occur on a dim array Computation of the XDR fit for red green is based on only X pairs of high PMT low PMT matching values This message appears if very few features had data in the overlap range for the fit The user should check the data in this case to confirm that the XDR combination is satisfactory e Computation of the XDR fit for red green results in a large intercept This message appears if the linear fit between the low and high intensity scans has a very large intercept This can be indicative of a poor linear fit The user should check the data in this case to confirm that the XDR combination is satisfactory e Computed XDR ratio for red green is X vs expected Y from PMT settings Check scanner calibration This message appears if the ratio of the high low intensity scans is different from what is expected from the scanner For instance an XDR scan set with 100 and 10 for PMT gain settings should yield a ratio close to 10 If this ratio is different than expected the Feature Extra
181. termined by multiplying a factor 1 42 by the interquartile range of the population made up of intra array feature replicates See Step 6 Reject outliers on page 181 166 Feature Extraction for CytoGenomics Reference Guide Table 18 Algorithms Protocol Steps and the results they produce continued Protocol Step Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Compute Bkgd Bias and Error Results BGAdjust BGused BGSubSignal IsPosAndSignif IsWellAboveBG SpatialDetrendlsin FilteredSet SpatialDetrend SurfaceValue Result Definition An adjustment value added to the initial background subtracted signal to correct for underestimation or overestimation of the background This value can be positive or negative Note the BGAdjust values are reported per channel in the STATS table of Feature Extraction text file Final background signal used to subtract the background from the feature mean signal To view the values used to calculate this variable using different background signals and settings of spatial detrend and global background adjust see Table 20 on page 190 Feature signal after subtraction of the background corrections To view the values used to calculate this variable using different background signals and settings of spatial detrend and global backgrou
182. text text float 15000 20000 30000 Feature Extraction for CytoGenomics Reference Guide Type output on page 156 for definitions Control type none Positive control Negative control SNP Not probe See Ch 4 for definition Ignore See Ch 4 for definition An Agilent assigned identifier for the probe synthesized on the microarray This is an identifier for the gene for which the probe provides expression information The target sequence identified by the systematic name is normally a representative or consensus sequence for the gene This is an identifier for the target sequence that the probe was designed to hybridize with Where possible a public database identifier is used e g TAIR locus identifier for Arabidopsis Systematic name is reported ONLY if Gene name and Systematic name are different Description of gene Found coordinates of the feature centroid in microns 115 Table 8 Feature results contained in the FULL output text file FULL FEATURES table continued Features Green LogRatio base 10 LogRatioError PValueLogRatio gSurrogateUsed glsFound 116 Features Red rSurrogateUsed rlsFound Types float float float float boolean Options 1000 Non zero value 0 1 IsFound 0 IsNotFound Description per feature log of rProcessedSignal gProcessedSignal If SURROGATES are turned off then if DyeNormRedSig lt 0 0 amp D
183. the BGSubSig2 Order Polynomial Zoom In of plot on left The effect of multiplicative detrending across array features A second order polynomial is fit to the higher signals on the array resulting in a subtle shape fit This fit results in the ProcessedSignal having a better fit to the data than the BGSubSignal Because the multiplicative trend can be confused with the additive trend for dim microarrays data points inside a multiple times the standard deviation from the center of the signals for the negative control population are excluded The equations for statistics and results that are produced by this calculation are shown in the following table See Table 18 Algorithms Protocol Steps and the results they produce on page 166 for descriptions of these results Feature Extraction for CytoGenomics Reference Guide 209 210 Table 22 Statistics and Results for Multiplicative Detrending Results Equation gMultDetrendRMSFit N MDS gt MDS average MDS MultDetrendSignal j N 21 gMultDetrendSignal of itted log 10 BgSubSignal N Fitted log 10 BgSubSignal 5 10 gl0 bg g yy t 1 N 22 gProcessedSignal BGSubSignal l _ 23 MultDetrendSignal gProcessedSigError BGSubSignalError l MultDetrendSignal Correct Dye Biases Step 21 Determine normalization features Normalization features are features used to evaluate the dye bias between the red and green channels Using All Prob
184. the next page 196 Feature Extraction for CytoGenomics Reference Guide Table 21 Statistical results of spatial detrend algorithm Result SpatialDetrendRMSFit SpatialDetrendRMSFiltered minusFit SpatialDetrendSurfaceArea Description and Equation This result gives an idea of the extent of the surface fit It is the root mean square of the fitted data points obtained from the Loess algorithm 12 This result is the approximate residual from the surface fit The deviations of the input filtered points from the corresponding output fitted data points are computed An outlier rejection is performed on the set of deviations using the standard IQR technique Figure 46 on page 188 Here is the value from the Loess fit and 0 is the BGSubSignal This result gives an idea of the curvature of the surface gradient Feature Extraction for CytoGenomics Reference Guide 197 198 Table 21 Statistical results of spatial detrend algorithm continued Result Description and Equation SpatialDetrendVolume The volume is calculated as the sum of the intensities of the surface area minus the offset The offset is calculated as the volume under the flat surface parallel to the glass slide passing through the minimum intensity point of the fitted surface This number total volume offset is normalized by the area of the microarray SpatialDetrendAveFit This describes the average intensity of the surface
185. thod in the protocol for calculating the spot value from pixel statistics is Median Normalized InterQuartile Range instead of Mean Standard Deviation the program makes these substitutions for the spot value and background subtraction calculations MedianSignal for MeanSignal BGMedianSignal for BGMeanSignal PixNorm IQR for PixSDev GPixNormlQR for BGPixSDev NormlQR 0 7413 x IQR If Median is the selection in the protocol the median is substituted for the mean in the inlierAve and the InlierSDev calculations Feature Extraction for CytoGenomics Reference Guide 191 192 Step 13 Perform background spatial detrending to fit a surface To calculate the spatial shape or surface for each channel the Feature Extraction program uses one of these background subtraction protocol selections e All Feature Types This selection fits the surface to a set of very low intensity features evenly distributed on the slide using a moving windowed filtering This algorithm which was the original algorithm for gene expression microarrays moves a window over the whole microarray and attempts to choose a fixed number of data points with the lowest intensity inside each window This option is recommended for those arrays without negative controls and is illustrated in the following figure No Moving Window Scatter Plot The effect of a moving window on selecting the lowest intensity features as an estimate of background In the figur
186. thresholds added Detrending turned off 26 Feature Extraction for CytoGenomics Reference Guide OC Report Headers Streamlined CGH QC Report The streamlined CGH QC report contains the same header information as the 2 color gene expression QC report except for Linear DyeNorm Factor and Additive Error which are removed Also the information from the two fields BG Method and Background Detrend have been collapsed into the one field BG Method CGH ChIP QC Report All header information that appears in the 2 color gene expression QC report are included in the CGH_ChIP report This report lists one additional metric Derivative of Log Ratio Spread in the header information Derivative of Log Measures the standard deviation of the probe to probe Ratio Spread difference of the log ratios This is a metric used in CGH experiments where differences in the log ratios are small on average A smaller standard deviation here indicates less noise in the biological signals Feature Extraction for CytoGenomics Reference Guide 2 Feature Statistics This section provides an explanation for each of the feature statistics segments of the QC report and how these feature statistics can help you assess the performance of your microarray system Spot Finding of Four Corners 28 By looking at the features in the four corners of the microarray you can decide if the spot centroids have been located properly If their locations
187. tion for CytoGenomics Reference Guide 63 64 CytoCcGH_QOCMT 8x Mar14 Metric Set Info Created On 20 Mar 2014 11 01 Type Agilent Description Removable False Metric Name IsGood6rid AnyColorPrentFeatWonU DerivatrveLR_Spread gRepro g_BGNotse g_Signal2Noise g_Signallntensity rRepro r_BGNoise r Signal2Noise rSignallntensity RestrictionContral LogRatiolmbalance Excellent gt I z1 0 20 0 to 0 10 lt 15 gt 100 gt 400 Oto 0 10 15 gt 100 gt 400 Good NA lto5 0 20 to 0 30 0 10 to 0 20 15 to 25 30 to 100 200 to 400 0 10 to 0 20 15 to 25 30 to 100 200 to 400 0 80 to 1 0 26 to 0 26 0 75 to 0 26 or 0 26 to 0 75 lt 1 gt 5 0 30 lt 0 or 0 20 25 lt 30 lt 200 lt 0 or 0 20 gt 25 lt 30 lt 200 lt 0 80 or gt 1 lt 0 75 or 0 75 Figure 33 QC Metrics for CytoCGH QCMT 8x _Mar14 metric set Feature Extraction for CytoGenomics Reference Guide Metric Set Info Created On Type Agilent Descingan Removable False Metric Name IsGoodGrid AnyColorPrentFeatWonuU DerivatrveLR_Spread gRepro g_BGNotse g_Signal2Noise g_Signallntensity rRepro rBGNoise rSignal2Noise rSignallntensity RestrictionControl LogRatiolmbalance Figure 34 Feature Extraction for CytoGenomics Reference Guide CytoCGH OCMT SingleCell_ Nov14 18 Nov 2014 14 41 Excellent gt 1 lt 1 0 to 0 10 0 to 0 10 Good NA lto5 lt 0 70 0 10
188. to determine if there are problems in the various laboratory steps label hybridization wash scan steps The new IsGoodGrid metric tracks the automatic grid finding of Feature Extraction By looking at a lot of data run on our arrays using our wet lab protocols Agilent has found thresholds that indicate if the data is in the expected range Good or out of the expected range Evaluate For some applications CGH miRNA an extra threshold level Excellent is provided More data has been screened to allow us to set the metric thresholds to a tighter limit that indicate excellent processing For those applications that do not have a full set of thresholds e g ChIP or no Excellent thresholds e g GE 1 and GE2 the user should be assured that the data coming from the Good grade is good to use Excellent thresholds for those applications may be provided in the future Feature Extraction for CytoGenomics Reference Guide OC metric set results default protocol settings Figure 3 is an example of part of a QC report the header and the Evaluation Metrics table generated from a 2 color gene expression extraction whose GE2 metric set with thresholds had been added In this extraction the default protocol settings were used Note that all values for the metrics are within the default threshold ranges QC Report Agilent Technologies 2 Color Gene Expression Date Saturday September 11 201
189. traction for CytoGenomics Reference Guide 171 Table 3 List of parameters and options contained within the FULL text output file FEPARAMS table Protocol Step Parameters Type Options Description Flag Outliers OutlierFlagger_ OLAutoComputeABC integer 1 True AutoCompute Outlier flagging turned on 0 False AutoCompute Outlier flagging turned off For Agilent protocols when this flag is turned on the polynomial is calculated automatically This means that all above Feature and BG terms for B and C no longer appear in the output Rather they are calculated automatically and appear in the STATS table Also the eight parameters following this row appear Flag Outliers OutlierFlagger_FeatBCoeff float Feature Red Poissonian Noise Term Multiplier Flag Outliers OutlierFlagger_FeatCCoeff float Feature Red Signal Constant Term Multiplier Flag Outliers OutlierFlagger_FeatBCoeff2 float Feature Green Poissonian Noise Term Multiplier Flag Outliers OutlierFlagger_FeatCCoeff2 float Feature Green Signal Constant Term Multiplier Flag Outliers OutlierFlagger_ BGBCoeff float Background Red Poissonian Noise Term Multiplier Flag Outliers OutlierFlagger_BGCCoeftf float Background Red Signal Constant Term Multiplier Flag Outliers OutlierFlagger_ BGBCoeff2 float Background Green Poissonian Noise Term Multiplier Flag Outliers OutlierFlagger_ BGCCoeff2 float Background Green Signal Constant Term Multiplier Flag Outliers OutlierFlagger_PopnO
190. troid is within the bounds of the spot deviation limit with respect to corresponding nominal centroid NOTE IsFound was previously termed IsStrong The propagated feature signal per channel used for computation of log ratio Standard error of propagated feature signal per channel Number of outlier pixels per feature with intensity gt upper threshold set via the pixel outlier rejection method The number is computed independently in each channel These pixels are omitted from all subsequent calculations Number of outlier pixels per feature with intensity lt lower threshold set via the pixel outlier rejection method The number is computed independently in each channel NOTE The pixel outlier method is the ONLY step that removes data in Feature Extraction Total number of pixels used to compute feature statistics i e total number of inlier pixels per spot same in both channels 147 Table 15 Feature results Full contained in the MAGE ML FEATURES table Quant Type Measur ed Signal SOT SQT Error SQT Measur ed Signal SQT Error SQT SQT 148 Features Green Green Measured Signal gMedianSignal gNetSignal Green PixSDev gBGNumPix Green Background gBGMedianSignal Green BGPixSDev gNumSatPix glsSaturated Features Red Options Red Measured Signal rMedianSignal rNetSignal Red PixSDev rBGNumPix Red Background rBGMedianSignal Red BG
191. ts 22 QC Report Headers 27 Feature Statistics 28 Histogram of LogRatio plot 41 QC Report Results in the FEPARAMS and Stats Tables 59 QC Metric Set Results 60 QC reports include statistical results to help you evaluate the reproducibility and reliability of your single microarray data Use plots and statistics from the report to e Set up your own run charts of statistical values versus time or experiment number to track performance of one microarray compared to other microarrays e Monitor upstream lab protocols such as performance of your hybridization washing steps e Monitor the effect of changing Feature Extraction protocol parameters on the performance of your data analysis If you incorporate a set of QC metrics in your extraction those results will appear on the final page of the QC report as an Evaluation Table fhe Agilent Technologies 21 OC Reports Streamlined CGH QC Report The streamlined CGH QC report provides QC metrics that are relevant to CGH application All log plots use log base 2 not 10 QC Report Agilent Technologies 2 Color CGH Date Friday September 10 2010 23 16 Sample red green User Name Administrator FE Version 10 10 0 23 Image Hu244K _CGH_251469312458 BG Method Detrend on NegC i ii Protocol 1 CGH_1010_Sep10 Read Only Multiplicative Detrend True 1 ac Re port Headers on Grid 014693_D_F_20100501 Dye Norm Linear Saturation Value 65211 r 65151 g page 27 DyeNorm List N
192. turated glsLowPMT Scaled Up glsFeatNonUnifOL Features Red rProcessedSigError rMedianSignal rBGMedianSignal rBGPixSDev rlsSaturated rlsLowPMTScaled Up rlsFeatNonUnifOL Types float float float float boolean boolean boolean Options 1 Saturated or 0 Not saturated 1 Low 0 High g r lsFeatNonUnifO L 1 indicates Feature is a non uniformity outlier in g r Description The universal or propagated error left after all the processing steps of Feature Extraction have been completed In the case of one color ProcessedSignalError has had the Error Model applied and will contain at least the larger of the universal UEM error or the propagated error lf multiplicative detrending is performed ProcessedSignalError contains the error propagated from detrending This is done by dividing the error by the normalized MultDetrendSignal Raw median signal of feature in green red channel inlier pixels Median local background signal local to corresponding feature computed per channel inlier pixels Standard deviation of all inlier pixels per local BG of each feature computed independently in each channel Boolean flag indicating if a feature is saturated or not A feature is saturated IF 50 of the pixels in a feature are above the saturation threshold Reports if the feature signal value is from the scaled up low signal image or from the high signal image Boolea
193. ture Extraction for CytoGenomics Reference Guide Table 13 Scan protocol parameters in MAGE ML result file continued Parameter Description MICRONS PER_PIXEL_Y Radius of pixel in the y direction GlassThickness Thickness of microarray slide Red DarkOffsetAverage Dark offset data per image in red channel as measured by scanner Green DarkOffsetAverage Dark offset data per image in green channel as measured by scanner PercentAutoFocusHold Amount of movement in the autofocus because of fluctuations in the glass DarkOffsetSubtracted Resulting signal when dark offset value is subtracted Table 14 Feature Extraction protocol parameters in MAGE ML result file Differences between FEPARAMS in text file and MAGE ML file Text File FEPARAMS MAGE ML File FEPARAMS Ratio _ErrorModel Error Model Ratio_AddErrorRed Red ADDITIVE_ERROR Ratio_AddErrorGreen Green ADDITIVE_ERROR Ratio_MultErrorRed Red MULTIPLICATIVE_ERROR Ratio_MultErrorGreen Green MULTIPLICATIVE ERROR For 1 color red signals and log ratios are not included in the MAGE ML output files Feature Extraction for CytoGenomics Reference Guide 145 Table 15 Feature results Full contained in the MAGE ML FEATURES table Quant Type SOT SOT Ratio Error PValue SQT 146 Features Green Features Red Options X_IMAGE_POSITION Y_IMAGE_POSITION SpotExtentX SpotExtentY LogRatio base 10 4 4 0 LogRatioError 1000 PValueLogRatio Non zero value 0
194. ture Statistics 42 Spike in probes are known probes that are hybridized with known quantities of a target spike in cocktail They are used to perform a quality check of the microarray experiment Some microarray designs have replicated non control probes that is multiple features on the microarray contain the same probe sequence Many of the Agilent microarray designs also have spike in probes which are replicated across the microarray e g some microarrays have 10 sequences with 30 replicates each The QC Report uses these replicated probes to evaluate reproducibility of both the signals and the log ratios Metrics such as signal CV and log ratio statistics are calculated if probes are present with a minimum number of replicates The protocol indicates if labeled target to these spike in probes has been added in the hybridization QCMetrics_UseSpikelIns The minimum number of replicates inliers to Sat amp NonUnif flagging is also set in the protocol QCMetrics_minReplicate Population This section provides an explanation for each of the segments of the QC report that cover inter feature statistics and how these replicate statistics can help you assess performance Reproducibility Statistics CV Replicated Probes Non control probes If a non control probe has a minimum number of inliers a CV percent coefficient of variation of the background corrected signal is calculated for each channel SD of signals
195. ture signals are adjusted so that very low level feature signals equal the protocol value Number of background subtracted features with negative signals 100 Feature Extraction for CytoGenomics Reference Guide Table 7 Stats results contained in the text output file STATS table continued Stats Green Channel gNonCtriNumNegFeatBGSub Sig gLinearDyeNormFactor gRMSLowessDNF DyeNormDimensionlessRMS DyeNormUnitWeightedRMS gSpatialDetrendRMSFit gSpatialDetrendRMS Filtered MinusFit gSpatialDetrendSurfaceArea gSpatialDetrendVolume gSpatialDetrendAveFit Stats Red Channel rNonCtriNumNegFeatBGSubSig rLinearDyeNormFactor rRMSLowessDNF rSpatialDetrendRMSFit rSpatialDetrendRMS Filtered MinusFit rSpatialDetrendSurfaceArea rSpatialDetrendVolume rSpatialDetrendAveFit Feature Extraction for CytoGenomics Reference Guide Type integer float float float float float float float float float Description Number of non control features with negative background subtracted signals Global dye norm factor The root mean square of the average lowess dye norm factor The lowess dye norm factor for each feature is its DyeNormSignal divided by its BGSubSignal Dimensionless RMS correction metric metric that indicates how much correction has been applied based upon the LOWESS curve Unit weighted RMS correction metric metric that indicates how much correctio
196. ulti pack and Third Party Hidden if Array Format is set to Automatically Determine Allow Some Distortion All formats Hidden if Array Format is set to Automatically Determine Set to False for all arrays except 30 microns single pack and multi pack for which it is set to True Hidden if Array Format is set to Automatically Determine Set to False for all arrays except 30 microns single pack and multi pack for which it is set to True Hidden if Array Format is set to Automatically Determine Set to False for all arrays except 30 microns single pack and multi pack for which it is set to True Automatically Determine Recognized formats 65 micron feature size 30 micron feature size and Third Party Hidden if Array Format is set to Automatically Determine True All Formats except Third Party False Third Party 14 Feature Extraction for CytoGenomics Reference Guide Table 1 Default settings for the preloaded CGH protocols Protocol Step Find Spots Parameter Spot Format Adjustment Threshold Maximum Number of Iterations Found Spot Threshold Number of Corner Feature Side Dimension Depending on the format selected by the software or by you the default settings for this step change See the rows below for the default values for finding spots Use the Nominal Diameter from the Grid Template Spot Deviation Limit Calculation of Spot Statistics Method Cookie Percentage
197. ults they produce 166 XDR Extraction Process 1 0 What is XDR scanning 1 0 XDR Feature Extraction process 170 How the XDR algorithm works 1 2 Troubleshooting the XDR extraction 1 73 How each algorithm calculates a result 1 4 Place Grid 1 4 Optimize Grid Fit 177 Find Spots 177 Flag Outliers 184 Compute Bkgd Bias and Error 190 Correct Dye Biases 210 Feature Extraction for CytoGenomics Reference Guide 10 Compute Ratios 215 Calculate Metrics 217 Example calculations for feature 12519 of Agilent Human 22K image 220 Data from the FEPARAMS table 221 Data from the STATS Table 221 Data from the FEATURES Table 221 Index Feature Extraction for CytoGenomics Reference Guide See the Agilent Feature Extraction for CytoGenomics User Guide to learn the purpose of all the parameters and settings and how to modify them Agilent protocols are meant for use with Agilent microarrays and are intended for use with arrays that use Agilent default lab procedures label hybridization wash and scanning methods The non Agilent protocol is meant for use with non Agilent microarrays that are scanned with an Agilent scanner Agilent CytoGenomics 3 0 Agilent Feature Extraction for CytoGenomics Reference Guide 1 Default Protocol Settings Default Protocol Settings Introduction 12 Default Protocol Settings 13 When a protocol is assigned to an extraction set the software loads a set of protocol parameter values and settings
198. utliers Parameters SpotAnalysis CentroidDiff SpotAnalysis_NozzleAdjust OutlierFlagger_Version OutlierFlagger_NonUnifOLOn OutlierFlagger_FeatATerm OutlierFlagger_FeatBTerm OutlierFlagger_FeatCTerm OutlierFlagger_ BGATerm OutlierFlagger_ BGBTerm OutlierFlagger_ BGCTerm Type Options Integer 1 True 0 False Integer 1 True 0 False text integer 1 True 0 False float float float float float float Description The software computes the per feature Centroid Difference between the Grid position and the Spot Center The software attempts to adjust a nozzle group in order to compensate for variations in printing Version of Outlier Flagger algorithm NonUniformity Outlier flagging turned on NonUniformity Outlier flagging turned off Applies to feature specifies the intensity dependent variance and is set to the square of the CV Applies to feature specifies the variance due to the Poisson distributed noise Applies to feature specifies variance due to background noise of the scanner slide glass and other signal independent sources Applies to background specifies the intensity dependent variance and is set to the square of the CV Applies to background specifies the variance due to the Poisson distributed noise Applies to background specifies variance due to background noise of the scanner slide glass and other signal independent sources Feature Ex
199. via the pixel outlier rejection method The number is computed independently in each channel These pixels are omitted from all subsequent calculations Raw median signal of feature from inlier pixels in green and or red channel The normalized Inter quartile range of all of the inlier pixels per feature The range is computed independently in each channel Boolean flag indicating if a feature is saturated or not A feature is saturated IF 50 of the pixels in a feature are above the saturation threshold Boolean flag indicating if a feature is a NonUniformity Outlier or not A feature is non uniform if the pixel noise of feature exceeds a threshold established fora uniform feature 137 Table 11 Feature results contained in the MINIMAL output text file MINIMAL FEATURES table Features Green Features Red Types Options glsFeatPopnOL rlsFeatPopnOL boolean g r lsFeatPopnOL 1 indicates Feature is a population outlier in g r glsWellAboveBG rlsWellAboveBG Boolean Description Boolean flag indicating if a feature is a Population Outlier or not Probes with replicate features on a microarray are examined using population statistics A feature is a population outlier if its signal is less than a lower threshold or exceeds an upper threshold determined using a multiplier 1 42 times the interquartile range i e IQR of the population Boolean flag indicating if a feature is WellAbove Background or not
200. visual results view shp file all spots that are found are shown using a blue X on the spot and marked as Found For all spots the blue cross shows the location of the grid If the centroid cannot be found because the spot is too weak or the distance between and X centroids exceeds the range specified by the Spot Deviation Limit this spot is labeled Not Found Feature Extraction for CytoGenomics Reference Guide 177 178 Step 4 Define features See the Agilent Feature Extraction for CytoGenomics User Guide for how the Feature Extraction program defines features either with the CookieCutter method or the WholeSpot method Step 5 Estimate the radius for the local background The radius is the distance from the center of the cookie or whole spot to the edge of the outermost region as shown in Figure 41 The default radius is the value specified in the protocol You can also enter a minimum radius whose value is less than the default radius or you can enter a larger radius to capture more pixels in the background You can use the radius method for estimating global backgrounds as well The figures in this step represent the local background for the CookieCutter method for defining features The radius for the local background is estimated in the same way for the WholeSpot method Feature or cookie Exclusion zone Local background Figure 41 Local background in relation to other zones for
201. voltage adjusts the spectral response of the scanner to incoming light from the lasers In general the higher the PMTVoltage the higher the signals will be for fluorescent artifacts that are scanned Typical numbers here are between 350 525 mV but can vary depending on the PMT Expressed in microns This represents the thickness of the microarray slide as measured during autofocus homing Using standard Agilent slides the values range from 900 1000 Nominal values for non Agilent slides are specified between 900 and 1100 for C scanners and 900 and 1200 for B scanners 111 Table 7 Stats results contained in the text output file STATS table continued Stats Green Channel RestrictionControl GridHasBeenOptimized ExtractionStatus OQCMetricResults UpRandomnessRatio DownRandomnessRatio UpRandomnesssSDRatio DownRandomnessSDRatio 112 Stats Red Channel Type float boolean 0 False 1 True integer 0 in range 1 out of range String float float float float Description Restriction control probes are a set of probes spanning cut sites that are not variant in samples If the protocol is followed correctly these probes should always give 0 signal The final restriction control value is the minimum of the restriction control values of red channel and green channel If restriction control probes are not present in the design the RestrictionControl value is set to
202. w calculation flag 0 False Place Grid GridPlacement_placementMode integer Mode of grid placement 0 Allow the grid to distort 1 Place the grid rigidly allowing only translation and rotation Optimize Grid Fit lterativeSpotFind_CornerAdjust integer Indicates whether or not the grid will be 0 False adjusted for better fit by looking at corner 1 True spots on the microarray Optimize Grid Fit IterativeSpotFind AdjustThreshold float Grid will be adjusted if absolute average difference between grid and spot positions is greater than this fraction Optimize Grid Fit lterativeSpotFind Maxlterations integer Maximum number of times spot finder algorithm is run to optimize the grid fit Optimize Grid Fit lterativeSpotFind FoundSpot float Grid will be adjusted if this fraction or more Threshold of the features are considered found by the spot finder algorithm Optimize Grid Fit lterativeSpotFind NumCornerFeatures integer Indicates the square area of features in each corner of the microarray to be used to calculate the average difference Find Spots SpotAnalysis Version text Version of the spot analysis algorithm Find Spots SpotAnalysis_weakthresh float Minimum difference between the average intensities of feature and background after Kmeans Initialization Find Spots SpotAnalysis_MinimumNumPixels integer Minimum number of pixels required for the spot analysis Find Spots SpotAnalysis_RegionOflnterest float Multiplier that defines how big the Region Multiplier of
203. w robust Count Avg and SD of these inliers for the net signal and the background subtracted signal g r NegCtrlNumInliers g r NegCtrlAveNetSig g r NegCtrISDevNetSig g r NegCtrlAveBGSubSig g r NegCtrlSDevBGSubSig Step 16 Determine the error in the signal calculation This step calculates the error on the background subtracted and detrended signal You can select for the error calculation either the Universal Error Model or the model Universal or propagated that produces the largest most conservative estimate of the error Feature Extraction for CytoGenomics Reference Guide The Feature Extraction program does a dynamic computation of an approximation for the additive terms in both the red and green channels for the Universal Error Model The estimation of the dynamic additive error term for each channel red or green is based on the following equation for l1 color gene expression the green channel AddError m ONegcy _ My DNF RMSFit m DNF residual 05 For definitions of non uniform and population outliers see the Feature Extraction for CytoGenomics User Guide The RMSFit term drops out of the equation for microarrays of less than 5000 features where m MultNcAutoEstimate M MultRMSAutoEstimate mz MultResidualkRMSAutoEstimate DNF LinearDyeNormF actor of the corresponding channel residual The residual of the 2D Loess fit Since the Additive Error is now calculated in Compute Backgroun
204. y is in the negative control range Indicates whether this feature was included in the set used to generate the multiplicative detrend surface Results are reported to 9 decimal places in exponential notation for all result files Feature Extraction for CytoGenomics Reference Guide 123 COMPACT Features Table Table9 Feature results contained in the COMPACT output text file COMPACT FEATURES table Features Green Features Red Types Options Description FeatureNum integer Feature number Row integer Feature location row Col integer Feature location column Sub TypeMask integer Numeric code defining the subtype of any control feature Control Type integer Feature control type See XML Control Type output on page 156 for definitions 0 Control type none 1 Positive control 1 Negative control 15000 SNP 20000 Not probe See Ch 4 for definition 30000 Ignore See Ch 4 for definition ProbeName text An Agilent assigned identifier for the probe synthesized on the microarray SystematicName text This is an identifier for the target sequence that the probe was designed to hybridize with Where possible a public database identifier is used e g TAIR locus identifier for Arabidopsis Systematic name is reported ONLY if Gene name and Systematic name are different Position X float Found coordinates of the feature Position Y centroid in microns 124 Feature Extraction for CytoGenomics Reference Guide Ta
205. yeNormGreenSig gt 0 0 if DyeNormRedSig gt 0 0 amp DyeNormGreenSig lt 0 0 if DyeNormRedSig lt 0 0 amp DyeNormGreenSig lt 0 0 If SURROGATES are turned off then if DyeNormRedSig lt 0 0 OR DyeNormGreenSig lt 0 0 IF SURROGATES are turned on then LogRatioError error of the log ratio calculated according to the error model chosen Significance level of the LogRatio computed for a feature The g r surrogate value used No surrogate value used A boolean used to flag found features The flag is applied independently in each channel A feature is considered Found if two conditions are true 1 the difference between the feature signal and the local background signal is more than 1 5 times the local background noise and 2 the spot diameter is at least 0 30 times the nominal spot diameter Feature Extraction for CytoGenomics Reference Guide Table 8 Feature results contained in the FULL output text file FULL FEATURES table continued Features Green gProcessedSignal gProcessedSigError gNumPixOLHi gNumPixOLLo Features Red Types Options rProcessedSignal float rProcessedSigError float rNumPixOLHi integer rNumPixOLLo integer Description The signal left after all the Feature Extraction processing steps have been completed In the case of one color ProcesssedSignal contains the Multiplicatively Detrended BackgroundSubtracted Signal if the detrending is selected and h
206. ype Options float float float float float float text text text text text text text text text text Description Space between rows on the grid Space between column on the grid In a dense pack array the offset in the X direction In a dense pack array the offset in the Y direction Nominal width in microns of a spot from grid Nominal height in microns of a spot from grid The build of the genome used to create the annotation if available If the genome build is not available not all designs have this information then it is not put out All recent and all future designs have it Barcode of the Agilent microarray read from the scan image Names of hybridized samples red green Name of the scan file used for Feature Extraction Microarray filename Design or grid file used for Feature Extraction Print file if available used for Feature Extraction Agilent pattern file name Time stamp at the beginning of Feature Extraction run for the extraction set Windows Log In Name of the User who ran Feature Extraction 72 Feature Extraction for CytoGenomics Reference Guide Table 3 List of parameters and options contained within the FULL text output file FEPARAMS table Protocol Step Parameters FeatureExtractor_ComputerName FeatureExtractor_ScanFileGUID FeatureExtractor_IsXDRExtraction DyeNorm_NormFilename DyeNorm_NormNumProbes Grid_IsGridFile Scan_Nu
207. ysis algorithms The Feature Extraction program places the grid on the high intensity scan only then finds spots using this grid on each of the two scans The XDR algorithm decides which features should use the low intensity scan data scales these signals appropriately and does a replacement for each feature and color channel where appropriate Then Feature Extraction proceeds with the rest of the data analysis outlier detection background correction dye normalization etc exactly as it would fora single non XDR scan Upon completion the Feature Extraction program generates results as if they were from a single measurement of the microarray The QC report and the stats table indicate that the Feature Extraction program extracted an XDR image pair by stating the new saturation value This is the saturation value of the low intensity scan after suitable scaling For instance if the high intensity scan is at 100 and the low intensity scan is at 10 the new saturation values will be around 650 000 about 10x greater than a normal 100 PMT gain scan This lets you use data in your calculations covering a much greater dynamic range 171 172 How the XDR algorithm works How does the XDR algorithm decide how to combine and scale the data from the high intensity and low intensity scans The general theory is that the high intensity gives the best results for the low end of the signal range and the low intensity scan gives better da

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