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Short Time-series Expression Miner (v1.2.1) User Manual

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1. for these time series experiments that profiles centered around 0 with high variance will be more likely to be considered significant in a permutation test that permutes this low variance time point 0 A permutation test that does not permute time point 0 can be useful here since profiles found to be significant under this 11 test are significant independent of the time point 0 expression value being known more accurately than that of the other time points In practice the set profiles found to be significant by either test will usually be similar e Correction Method The significance level can be corrected for the fact that multiple profiles are being tested for significance The correction can be a Bonferroni correction where the significance level is divided by the number of model profiles or the less conservative False Discovery Rate control 2 If none is selected then no correction is made for the multiple significance tests Note that this parameter for multiple test correction for model profiles is unrelated to the corrected p values in a GO enrichment analysis 3 3 3 Clustering Profiles Options Advanced Options Filtering Model Profiles Clustering Profiles Gene Annotations GO Analysis Minimum Correlation 07 H Minimum Correlation Percentile repeat onb 1S m Figure 8 The above panel is used to specify options for grouping statistically significant model profiles The two par
2. AAW MAe VABCOOEBSEN i ja LL a es Sas lie AUAN NH ANANN AMANE A A A IM AV MI SIMA MW All rofile a mea ai SS ANNA bol bo WE AIA IM AES EO EIEN eM WG VIE hd fd EM EMI EV MWA by m Filtered Gene List _ Main Gene Tabie _ Interface Options Order Profiles By Order CustersBy __Compare A iles 1 OX Profiles ordered based onthe expected number of genes based on a permutation test EM EVI Ev had WS AL MUM MRS EM EMILY DLA EWE KES EMI BY RN IAA S Filtered Gene List_ Main Gene Tabie _ Intertace Options Order Profiles By Order CustersBy __Compare 2 Filtered Gene List_ Main Gene Tabie _ interface Options Order Profiles By Order CustersBy __Compare Figure 17 Top left Profiles are ordered by ID Top right Profiles are ordered based on significance Bottom left Profiles are ordered based on number of genes assigned Bottom right Profiles are ordered based on the expected number of genes assigned 22 Define Gene Set Sel Gene Name In Gene Set BCAG BCA BCA BCB10 ABCC13 BCC2 BCC3 BCC5 BCC6 BCD3 BCD4 BCE1 BCF1 R K il _ __Gene Name _ ABCC13 Profile ID in Comparison Set 25H Select Genes Query Gene Set Load Gene Set Save Gene Set Figure 18 Dialog window through which to specify a user defined gene set Genes which are checked are part of the set 23 4 4 Ordering Clusters of Pro
3. PRPFS G0 0008246 60 0006397 50 0005634 G0 00056872 3 PRPF4 G0Q 0008246 G0 0000399 G0 0008380 GO 0005681 4 JMJD26 GO 0003677 GO 0006355 5 WJMJD2A GO 0003677 GO 0006355 6 AOKT GO 0004031 GO 00046854 G0 0005489 G0 0016491 GO 0030151 GO 0006118 GO 0006600 GO 0006954 7 OBP2B G0O 0005215 G0 0005549 GO 0000004 G0 0006810 G0 0007608 GO 0007635 G0 0008372 8 OBP2ZA GO 0005215 60 0005549 GO 0000004 S0 0006910 S0 0007608 GO 0008372 3 PNUF GO 00048606 GO 0016767 G0 0006641 GO 0016042 10 STKE GO 0004674 G0 0005524 G0 0016740 G0 0006468 GO 0007049 G0 0007067 G0 0005634 G0 0005819 Figure 5 Annotation file in a two column format The first column contains gene symbols or spot IDs while the second column contains category IDs Annotation files can also be in the official 15 column format In the second section of the interface a user specifies the gene annotation information Both gene symbols or spot IDs can be annotated as belonging to an official Gene Ontology GO category or a user defined category If a gene is annotated as belonging to an official category in the Gene Ontology then it will automatically also be annotated as belonging to any ancestor category in the ontology hierarchy The first field in this section of the interface is the Gene Annotation Source This field can be set to either User provided No annotations or one of 35 annotation data sets provided by Gene Ontology Consortium members A full list of the 35 data sets c
4. 28 which if pressed again will revert the window back to its original state Profile 43 Profile 43 0 1 3 3 2 150 0 Genes Assigned 28 5 Genes Expected p value 0 00 significant Query set profile enrichment uncorrected p value 4 2E 5 8 0 150 0 vs 173 20452 6 7 genes 5 Expression Change v v 0 Figure 27 An example of a model profile detailed information window that appears when the profiles are ordered based on query set enrichment 32 Profile 9 Profile 9 Profile 9 0 1 2 3 4 Profile 9 0 1 2 3 4 3 Expression Change 3 Expression Change v i v 0 130 0 Genes Assigned 34 7 Genes Expected p value 0 00 significant v i v 0 130 0 Genes Assigned 34 7 Genes Expected p value 0 00 significant Figure 28 If the model profile window is opened from the main gene table then there will be an option to plot just the gene selected The image on the left initially appears but pressing Click to plot only gene STAM2 replots with only the gene STAM2 33 5 1 Gene Table Weight Gene Symbol SPOT 1 00 SLC1A3 41 1 00 MCME 1310 1 7642 1 00 PDGFRA 1669 1 00 MGC5576 1726 1 00 0 SPOT_2390 2390 1 00 CDK 284519180 1 00 MCM5 2856 14160 16303 1 00 KIAA0152 3077 1 00 FLJ11565 3244 1 00 _ SNX5 3255 1 00 0 SPOT_3614 3614 B Copy Table Save Table B Copy Gene Names Save
5. Gene Names Figure 29 The above window is a gene table for a profile From a model profile details interface window a user has the option to open or more gene tables such as the table that appears in Figure As discussed in the beginning of the section which genes appear in the table depends upon which button was pressed to open the table A gene table has the following columns e Selected This is the same column as in the main gene table An entry in this column contains a Yes if the gene of the row is part of a category or gene set by which the profiles are ordered otherwise the field is empty e Weight This field represents the weight of the assignment of the gene to the profile If the profile the gene most closely matches is unique then the value is one If there is a tie as to which profile a gene most closely matches then this value is one divided by the number of profiles a gene most closely matches e Gene Symbol This column contains the gene symbols The name for this column is read from the header in the data file e Spot ID An entry in this column contains a list of spot IDs of spots which contain the gene of the row delimited by a The header for this column is read from the data file if spot IDs are included in the data file e Time Point columns The time series of gene expression levels for the gene after any selected transformation Log normalize data Normalize data or
6. ID An entry in this column contains a list of spot IDs of spots which contain the gene of the row The entries are delimited by a The header for this column is read from the data file if spot IDs are included in the data file 16 p value ofthe enrichment of genes in the selected GO category or query set assigned to profiles of this color fonly appears if reordering by clusters Colored profiles have a statistically significant number of genes assigned odel profile of log of expression change ratio over time Lower left hand corner contains information relevant to the current reordering of profiles f ordering by significance this will be the p value of number of genes assigned versus expected f ordering by number of genes assigned this will be the number of genes assigned to the profile f ordering by expected number this will be the expected number of genes af this profile based on a permutation test f ordering based on a GO category or query set enrichment then this will be the number of genes in the selected GO category or set and assigned to this profile then a semicolon and then the uncorrected p value for the enrichment Figure 12 The legend that appears after pressing the help icon Table of Genes Passing Filter Seles Selected Gene Symbol Protile On 0 5 3h BA 12 OSCR TL 38 0 00 0 96 0 66 1 16 1 08 Ce aa 01 EE Cen 35 osz jos B E 0 53 oo Cm0RBe Bt BL BARB DABS e BT e a BIRC
7. If the input data file already represents the log ratio of a sample against a control as is often the case when the data is from a two channel cDNA array and an experiment was conducted at time point 0 then the Normalize data option should be selected In this case after normalization the transformed values will represent the log change ratio versus time point 0 If the input data file already contains log ratio data against a control but no time point 0 experiment was conducted then the No normalization add 0 option should be selected In this case the assumption is made that had a time point 0 experiment been conducted the expression level in both channels would have been equal Repeat Data Files Repeat Data File s 2 _2 txt Repeat Data is from Different time periods The same time period sawr Remove File View Selected File OK Figure 4 The above window is used to specify repeat data files A user can add or remove repeat files with the Add File and Remove File buttons A user also needs to specify whether the repeat data samples are from the same time period or different time periods as the original data The contents of a repeat file can be viewed by selecting the repeat file and then pressing the View Selected File button Pressing the Repeat Data button brings up an interface as shown in Figure 4 The Repeat Data button on the main input interface is yellow if there is currently one or more
8. a graph of all genes assigned to the profile The text at top gives information about the profile including the number of genes assigned the number of genes expected and the p value significance The Profile Gene Table button displays a table of genes assigned to the profile while the Cluster Gene Table displays a table of genes assigned to any profile in the profile s cluster of profiles The Profile GO Table displays a gene category enrichment for genes assigned to the profile while Cluster GO Table displays a gene category enrichment for genes assigned to any profile in the profile s cluster of profiles 30 second ratio the numerator C contains the total number of genes in the category or user defined gene set The denominator in the second ratio D is the total number of genes on the array The number to the right of the second ratio after the semicolon is the number of genes the profile is enriched for and is computed as A B x E If the cluster of profiles are reordered based on a category or a user defined gene set then an additional line appears below the profile enrichment line about the category enrichment computed based on the set of genes assigned to any profile in the cluster Along the bottom of the window are several yellow buttons Which buttons appear will depend upon how the profiles are ordered through which interface the window was opened and whether the profile is part of a non singleton cluster of p
9. be made This algorithm is guaranteed to converge to a local minimum but not a global minimum The algorithm can be repeated for a number of different random starts with potentially a different clustering obtained from each start Only the run with the best scoring final set of clusters is returned The number of random starts is specified in the field Number of Random Starts on the main input interface Increasing this parameter leads to a potentially slightly better clustering at the expense of a slightly longer running time After the K means algorithm executes the main output interface is displayed see Figure 38 This interface is similar to the model profile overview interface described in Section 4 with a few differences of note For K means clustering each box on the interface corresponds to a cluster instead of a profile The time series shown in the box is the average expression of all genes assigned to the cluster The number in the top left hand corner of the box is a Cluster ID see Figure for a legend All K means cluster boxes appear white since no statistical significance is associate with them The K means cluster are by default ordered based on ID IDs are assigned based on the cluster average expression value at the first time point AK means cluster boxes can be reorder on the main interface analogous to the reordering of STEM profile boxes described in Section 4 3 Pressing the Interface Options butt
10. between real and random patterns STEM is also integrated with the Gene Ontology GO 4 allowing efficient biological interpretations of the data 1 1 STEM Clustering Method Overview The novel clustering method that STEM implements first defines a set of distinct and representative model temporal expression profiles independent of the data These model profiles correspond to possible profiles of a gene s change in expression over time The model profiles all start at 0 and then between two time points a model profile can either hold steady or increase or decrease an integral number of time units up to a parameter value Gene expression times series are transformed to start at 0 and each gene is assigned to the model profile to which its time series most closely matches based on the correlation coefficient The number of genes assigned to each model profile is then computed The number of genes expected to be assigned to a profile is estimated by randomly permuting the original time point values renormalizing the gene s expression values then assigning genes to their most closely matching model profiles and repeating for a large number of permutations The average number of genes assigned to a model profile over all permutations is used as the estimate of the expected number of genes assigned to the profile The statistical significance of the number of genes assigned to each profile versus the numbe
11. e Category ID The ID for the category e Category Name The name for the category e Genes Category The number of genes on the entire microarray that were annotated as belonging to the category e Genes Assigned The number of genes annotated as belonging to the category that are part of the set of genes being analyzed 30 Genes Expected The number of genes annotated as belonging to the category that were expected to be part of the set being analyzed This value will depend on whether an actual size or expected size profile enrichment analysis is being conducted e Genes Enriched The difference between Genes Assigned and Genes Expected e p value The uncorrected p value of seeing this many or more genes from this category assigned to the set of genes being analyzed This p value will depend on whether an actual size or expected size enrichment analysis is being conducted See Section for a discussion on how the p value is computed e Corrected p value The p value corrected for testing a large number of GO categories If the enrichment is based on a set s actual size and Randomization is selected as the value for Multiple hypothesis correction method for actual size based enrichment the corrected p value is computed based on a randomization test If the enrichment is computed based on a set s expected size or Bonferroni is selected as the value for Multiple hypothesis correction
12. in which case it will be downloaded from ftp ftp ebi ac uk pub databases If the Cross References box is checked then the file listed in the Cross Reference File box will be downloaded from ftp ftp ebi ac uk pub databases GO goa If the Ontology field is checked then the file gene_ontology obo will be downloaded from http www geneontology org ontology gene_ontology obo If the annotation cross reference or ontology file is required for use and not present in the stem directory then the corresponding field will be checked and there will not be an option to uncheck the field forcing download of the file s If the Gene Annotation Source is set to User Provided then there will not be an option to download the gene annotation file and likewise for the cross reference source field and cross reference file Upon pressing the execute button the files corresponding to the checked fields will be downloaded 3 3 Options In the third section of the interface a user has the option to specify a variety of execution options for STEM The first option a user specifies is the Clustering Method which can be set to either STEM Clustering Method or K means The STEM clustering method is the novel clustering method STEM implements specifically designed for short time series expression data briefly described in Section 1 1 and described in more detail in 3 STEM s implementation of the K means algorithm is discussed in Section 7 Assu
13. is determined by the entry in the Aspect field Column 9 An entry of P in the Aspect field means the annotation is of type Biological Process an entry of F means the annotation is of type Molecular Function and an entry of C means the annotation is of type Cellular Component e Only include annotations with these taxon IDs Some annotation files contain annotations for multiple organism and it might be desirable to use only annotations for certain organisms To use only annota tions for certain organisms enter the taxon IDs for the desired organisms delimited by either commas semicolons or pipes If this field is left empty then any organism is assumed to be acceptable More information about taxonomy codes and a search function to find the taxon code for an organism can be found at Note that this parameter only applies when the annotations are in the official 15 column format The taxonomy ID in the annotation file is in column 13 of the file and the taxon IDs entered in this parameter field must match the entry in column 13 or match after prepending the string taxon to the ID For example to use only annotations for a Homo sapien the string 9606 can be used e Exclude annotations with these evidence codes This field takes a list of unacceptable evidence codes for gene annotations delimited by either a comma semicolon or pipe If this field is left empty then a
14. of genes assigned to the cluster As with reordering profiles one can reorder a cluster of profiles by a user defined gene set by pressing the button Define Gene Set and then using a dialog such as appeared in Figure The expected number of genes in a cluster being analyzed is not well defined since the clusters of profiles are defined based on the data When clusters of profiles are reordered based on a category or user defined gene set the p value enrichment for the cluster of profiles appears in the top right hand corner of the profile box of each profile that is part of the cluster The number of genes of the category assigned to the profile and the p value enrichment still appear in the lower left hand corner of the profile box The Default Order button returns the profiles to their initial ordering as explained in Section 4 3 4 5 Interface Options Interface Options Gene display policy on main interface O Do not display Display only selected w Display all Change Color of Genes Y axis scale for genes on main interface should be O Gene specific Profile specific Global Scale should be based on only selected genes Y axis scale on profile details windows should be Determined automaticaly Fixed with parameters below Min H Max JH Tick interval H X axis scale should be O Uniform Based on realtime Figure 21 The window to adjust interface options that appears when pres
15. on the button Click for GO Results Based on the Profile s Expected Size opens another table with GO results computed based on the expected size of a profile file Figure 30 shows an example of such a table As discussed at the beginning of the section the exact set of genes that the enrichment analysis is for depends upon which button was pressed to bring up the table For a category to appear in the table the number of genes in the set of genes being analyzed that belong to the category must be greater than or equal to the value of the Minimum number of genes parameter on the GO Analysis panel under Advanced Options For official GO categories the level of the category must be greater than or equal to the value of the Minimum GO level parameter also on the GO Analysis panel under Advanced Options As discussed in Section 4 3 there are two ways to compute gene enrichment one based on the actual size of the set and the other based on the expected size of the set For clusters of profiles gene enrichment is always based on the actual size of the set For profiles gene enrichment by default is based on the actual size of the set However there will be a button along the bottom of the window which says Click for GO Result s Based on the Profile s Expected Size that when pressed will open a new table where the enrichment analysis is based on the profile s expected size The columns of a gene enrichment table are as follows
16. right and top to bottom based on the significance of the enrichment for the selected category The profile most enriched for the selected category appears in the top left corner The next most enriched profile appears second in the top row and so on For instance Figure 16 shows an example of the model profiles reordered based on an actual size enrichment for cell cycle genes The numbers that appear in the bottom left hand corner of the model profile box are the number of genes assigned to the profile that also belong to the selected category and then separated by a semicolon the p value enrichment Below the table are several buttons which give additional criteria to reorder profiles 20 e Profile ID Reorders profiles sequentially from left to right and top to bottom by their ID number the number in the top left corner of the profile box top left Figure 17p Profiles which go down initially will appear first then profiles which hold steady initially and then last will be profiles which go up initially e Significance Reorders profiles based on the p value significance of number of genes assigned to a profile being more than the number of genes expected top right Figure 17 If Sa genes were assigned to the profile and se genes were expected and a total of t genes passed filter then the uncorrected p value of seeing Sa or more genes assigned to the profile is computed based on a binomial distribution wit
17. the ms512M option with ms1024M e STEM can be started with its initial settings specified in a default settings file The format of a default setting file is specified in Appendix A To have STEM load its initial settings from a default settings file from the command line append d followed by the name of the default settings file to the above command For instance to have STEM start with the settings specified in the file defaults txt use the command java mx1024M ms512M jar stem jar d defaults txt 3 Input Interface The first window that appears after STEM is launched is the input interface Figure I The interface is divided into four sections In the top section a user specifies the expression data files and normalization options for the data In the second section a user specifies the gene annotation information In the third section a user specifies the desired clustering algorithm and various execution options These three sections of the interface are described in more detail in the next three subsections In the fourth section of the interface there is a button which when pressed causes STEM to execute the selected clustering algorithm and then display the output interface described STEM Short Time series Expression Miner 1 Expression Data Info Data Fue 927184 Browse View Data File E O Log normalize data Normalize data C No normalization add 0 v Spot IDs included in the data file H 2 Gene An
18. to both the category of interest and assigned to the profile of interest can be computed as min m sq A Sm gt a Sq 1 a If the enrichment is computed based on a profile s expected size Se then the p value of seeing more than v genes belonging to both the category and profile of interest can be computed based on a binomial distribution with parameters m and 5 as i N N t V If a profile has more genes assigned than expected then it is possible a gene enrichment for a category will be significant under an expected size based enrichment while it is not significant under an actual size enrichment Likewise if a profile has fewer genes assigned than expected it is possible a gene enrichment for a category will be significant under an actual size based enrichment while it is not significant under an expected size based enrichment If multiple independent processes happen to have the same temporal profile then a significant gene enrichment for the process may be missed through an actual size enrichment but detected through an expected size enrichment Clicking on a row of the table will reorder the profiles based on the p value enrichment for the category of that row Whether the p value enrichment is computed based on the profile s actual size or expected size will depend on which is selected next to the label Order using enrichment p values based on a profile s Profiles are ordered row wise from left to
19. 07049 cell cycle g S Elissa Bo EN bw Eo bo WS rN bo be id bel ke het bA be SMA A MAIO ba bw by Eo AAN eM Bod Cd RN MAA CVEN Eo BY EN Figure 20 Cluster of profiles ordered based on enrichment for cell cycle genes When a user presses the Order Clusters By button on the main profile window a dialog box such as in Figure 19 appears This window is a simplified version of the window that appears when a user presses Order Profiles By Through this dialog box a user can reorder the cluster of profiles A cluster of profiles is either a singleton profile or a group of profiles which all have a statistically significant number of genes assigned and are all similar to each other as defined based on parameters on the Clustering panel under Advanced Options Profiles of the same cluster have the same color on the main profile window When clusters of profiles are reordered profiles of the same cluster are kept next to each other as appears in Figure 20 Also when reordering clusters of profiles all non statistically significant profiles are also reordered but always appear after the cluster of statistically significant profiles As with reordering profiles discussed in the previous subsection it is possible to reorder the cluster of 24 profiles by gene enrichment for any category that appears in the table by clicking on the row of the category The gene enrichment for a cluster of profiles is always computed based on the number
20. 3 4E 10 regulation of progression through cell cycle 4 7E 10 regulation of cell cycle DNA replication nucleobase nucleoside nucleotide and n DNA dependent DNA replication nucleus DNA repair cellular physiological process biopolymer metabolism primary metabolism 5 2E 7 response to DNA damage stimulus 5 6E 7 intracellular part 9 0E 7 cell part 9 4E 7 j q 5E 7F Order using enrichment p values based on a profile s actual size expected size Profile ID Significance Number of Genes Expected Number Default Order Define Gene Set Copy Table Save Table Figure 15 The dialog box through which the profiles can be reordered on the model profile overview interface Clicking on a row of the table reorders the profiles by gene enrichment for genes of that category AILSTEM Profiles 1 Profiles ordered based onthe actual size based p value of gene enrichment of GO 0007049 cell cycle genes saN PARE wa aa al _ ICICI aie al Figure 16 The main profile window with the profiles reordered by the actual size based p value enrichment for cell cycle genes The two numbers in the bottom left hand corner of each profile box are the number of cell cycle genes assigned to that profile and then separated by a semicolon is the p value of the gene enrichment for cell cycle genes in the profile 19 an entry for every category containing at least one gene passing filt
21. Data_is_from Different time periods The same time period Different time periods Comparison Data Comparison_Data_File compare txt Comparison_Maximum_Uncorrected_Intersection_pvalue 005 Comparison_Minimum_Number_of_genes_in_intersection 5 Comparison_Repeat_Data_Files comma delimited list Comparison_Repeat_Data_is_from Different time periods The same time period Different time periods Filtering Maximum_Number_of_Missing Values 0 Minimum_Correlation_between_Repeats 0 Minimum_Absolute_Log_ Ratio_Expression 1 Change_should_be_based_on Maximum Minimum Difference From 0 Maximum Minimum Pre filtered_Gene_File Model Profiles Maximum _Correlation 1 Number_of_Permutations_per_Gene 50 48 Maximum_Number_of_Candidate_Model_Profiles 1000000 Significance_Level 05 Permutation_Test_Should_Permute_Time_Point_0O true Correction_Method Bonferroni False Discovery Rate none Bonferroni Clustering Profiles Clustering Minimum_Correlation 0 7 Clustering Minimum_Correlation_Percentile 0 Gene Annotations Category_ID_file Include_Biological_Process true Include_Molecular_Function true Include_Cellular_Process true Only_include_annotations_with_these_evidence_codes Only_include_annotations_with_these_taxon_IDs GO0 Analysis Minimum_GO_level 3 GO_Minimum_number_of_genes 5 Number_of_samples_for_randomized_multiple_hypothesis_correction 500 Multiple_hypothesis_correction_method_enrichment Bonferroni Randomization Rando
22. Ds Spot IDs uniquely identify an entry in the data file and if they are not included in the data file then they will be automatically generated While spot IDs must be unique the same gene symbol may appear multiple times in the data file corresponding to the same gene appearing on multiple spots on the array Expression values for the same gene will be averaged using the median before further analysis on the data is conducted A sample data file as it would appear in Microsoft Excel is shown in Figure 2 The first column which appears in yellow is optional and if included contains spot IDs If the data file includes the spot IDs column then the field po A B D E F CG Gene Symbol Oh 0 5h 3h 6h 12h ZFX 0 027 0 158 0 169 0 193 0 165 ZNF133 0 183 0 068 0 134 0 252 0 177 USP2 0 67 0 709 0 347 0 779 0 403 DSCRIL1 0 923 0 51 0 718 0 512 0 669 WNTSA 0 471 0 264 0 269 0 154 0 254 TIMP 0 111 0 351 0 168 0 129 0 293 11 SERPINA 0 468 0 4858 0 199 0 144 0 185 Figure 2 Above is a sample input data file when viewed in Microsoft Excel The first column shown in yellow contains spot IDs and is optional If the column is included then the field Spot IDs included in the data file on the input interface must be checked otherwise the field must be unchecked and the first column contain gene symbols The columns containing the time series of gene expression values come after the gene symbol
23. Gene List button displays a table of genes that were filtered and thus not assigned to a model profile The Main Gene Table button displays a table of genes that were not filtered and thus assigned to a model profile The Interface Options button displays a window in which one can adjust various interface options The Order Profiles By button opens a dialog window that allows one to reorder the model profiles on the main overview screen by a number of criteria The Order Clusters By button opens a dialog window that allows one to reorder the clusters of profiles that is profiles are reordered with the constraint that profiles of the same color must be kept together The main gene table the filtered gene list ordering profiles ordering clusters of profiles and interface options are explained in detail in the next five subsections The Compare option which allows comparison with a data set from a different experimental condition is explained in Section 6 Pressing the help icon brings up the legend that appears in Figure 12 along 15 AILSTEM Profiles 1 Clusters ordered based on number of genes and profiles ordered by significance default BALACA SEIN ANMINAN SI MIM MMA NIMIMA Aw VA eR WWI AA Filtered Gene List_ Main Gene Table _ Interface Options Order Profiles By Order Custers By _Compare 2 Figure 11 An example of the main profile overview interface Each box corresponds to a model express
24. H P28 beroa BR Bt BLOT BO TA af I e e E Cc a aa a I Copy Table Save Table Copy Gene Names Save Gene Names Figure 13 An example of a table that appears after pressing Main Gene Table The table includes all genes that were not filtered and thus assigned to a model profile 17 e Profile s Assigned The ID of the model profile or in the case of a tie the profiles for which the gene s expression pattern most closely matched and thus to which the gene was assigned e Time Point columns The time series of gene expression levels for the gene after any selected transformation Log normalize data Normalize data or No normalization add 0 The header for these columns are read from the data file This table as all tables in STEM can be sorted by any column Click once on a column header to sort the table in ascending order by that column s values Click twice on the column header to sort the table in descending order and a third time to return the table to its original order To cycle through the sorting options in the opposite order hold down the Shift button when clicking To do a compound sort on multiple columns hold down the Ctrl button when clicking Also as with all tables in STEM a user can save the contents of the table by pressing the Save Table button or copy the contents to the clipboard with the Copy Table button As with any gene table in STEM a user can also just save the list of gene names u
25. No normalization add 0 The header for these columns are read from the data file As with all tables in STEM this table can be sorted in ascending or descending order by any column by clicking on the column header A user can also save the entire table using the Save Table button or just the gene names using the Save Gene Names button Likewise a user copy the entire table to the clipboard using the Copy Table button or just the gene names using the Copy Gene Names button 5 2 Gene Enrichment Analysis Table From the window with details about a model profile a user has the option to display a table that includes gene enrichment for Gene Ontology GO categories along with any other categories that may appear in an annotation 34 Category ID Category Name Genes Category Genes Assigned Genes Expected Genes Enriched p value Corrected p value Go 0007049 cell cycle 427 20 0 17 3 3 2E 12 0 001 DNA metabolism regulation of progression through cell cycle regulation of cell cycle DNA replication 106 nucleobase nucleoside nucleotide and nuc 1456 DNA dependent DNA replication 48 nucleus 1631 DNA repair 135 cellular physiological process 4298 biopolymer metabolism 1265 primary metabolism 3064 response to DNA damage stimulus 152 intracellular part 3244 response to endogenous stimulus 162 intracellular 3426 intracellular membrane bound organelle 2435 membrane bound orga
26. STEM Short Time series Expression Miner v1 2 1 User Manual Jason Ernst jernst cs cmu edu Ziv Bar Joseph Machine Learning Department School of Computer Science Carnegie Mellon University Contents 1 Introduction 1 1 STEM Clustering Method Overview 0 0 0 0 1 2 Manual Overview 1 3 Citing STEM 2 Preliminaries 3 Input Interface 3 1 Expression Data Info 3 2 Gene Annotation Info Soe ee ees we Aeoa se 3 3 1 Filtering Options 7 z 4 Model Profiles Overview Interface 4 1 Main Gene Table aaa 4 2 Filtered Gene List 4 3 Ordering Profiles 4 4 Ordering Clusters of Profiles 4 5 Interface Options 4 6 Zooming and Panning 5 Model Profile Details Interface 5 1 Gene Table 02 22 5 2 Gene Enrichment Analysis Table 7_K means A Defaults File Format B Using STEM for Standard Gene Ontology Enrichment Analysis C Gene Annotation Sources 10 12 13 14 15 16 18 18 24 25 29 29 34 34 37 42 48 50 51 1 Introduction Welcome to STEM STEM is an acronym for the Short Time series Expression Miner a software program designed for clustering comparing and visualizing gene expression data from short time series microarray experiments 8 time points or fewer STEM implements a novel method for clustering short time series expression data that can differentiate
27. ameters on the clustering profile panel shown in Figure 8 control the grouping of significant model profiles into clusters The parameters on this panel are again only relevant to the STEM clustering method and not K means clustering The parameters control how similar two model profiles must be if they are grouped together The two parameters are as follows e Minimum Correlation Any two model profiles assigned to the same cluster of profiles must have a correla tion above this parameter s value Increasing this value will lead to more clusters with fewer model profiles per cluster while decreasing the value will lead to fewer clusters with more model profiles per cluster e Minimum Correlation Percentile If there is repeat data selected to be from Different time periods then this parameter specifies that any two model profiles assigned to the same cluster of profiles must have a correlation in their expression greater than the correlation of this percentile in the distribution of gene expression correlations between the repeats For instance if this parameter value is 0 5 then any two model profiles assigned to the same cluster will have a correlation greater than the median correlation of gene expression correlations between the repeats This parameter allows clustering of model profiles to be dependent on the noise in the data If the Minimum Correlation parameter is set to 1 then only the Minimum Correlation Percentil
28. ample of which is shown in 37 Comparison Significant Intersections Original Set Profiles Original Set Profiles u w E E a a t D N N c O oO w w Ce Q a E E a o O O Figure 33 The main comparison window If a profile appears to the right of the yellow bar then a significant number of genes assigned to the profile were also assigned to the profile to the left of the yellow bar in the other experiment Figure The window shows all profile pairs containing a gene intersection satisfying the size and p value constraints specified on the comparison dialog The interface layout has two halves with a blue bar separating the two halves there is no significance associated with a profile appearing to the left or right of the blue bar If the vertical text label on the left side of each half read Original Set Profiles then to the immediate left of the vertical yellow bar are profiles all of which are from the original data set If the vertical label reads Comparison Set Profiles then the profiles to the left of the yellow bar are all from the comparison data set To the right of the yellow bars are profiles from the other data set If the profiles to the right of the yellow bar are from the comparison experiment then the horizontal labels on the top of the screen will read Comparison Set Profiles while if the profiles to the right of the yellow bar are from the original experiment then the horiz
29. an be found in Appendix C More information about these annotation sets can be found at and for the annotation sets provided by the European Bioninformatics Institute EBI also at One of the 35 data sets is the EBI UniProt set Subsets of this data set with annotations specific to a large number of organisms can be found at www ebi ac uk GOA proteomes html and are not included in the list of 35 data sets If one of the 35 data sets is selected then the annotation file corresponding to the source will appear in the Gene Annotation File text box uneditable If User provided is selected then the Gene Annotation File text box will become editable and a user can specify a gene annotation file Selecting No annotations is equivalent to selecting User Provided and leaving the field empty A gene annotation file can be in one of two formats 1 The gene annotation file can be in the official 15 column gene annotation file format described at All 37 of the data sets provided by Gene Ontology Consortium members are in this format If the file is in this format any entry in the columns DB_Object_ID Column 2 DB_Object_Symbol Column 3 DB_Object_Name Column 10 or DB_Object_Synonym Col umn 11 will be annotated as belonging to the GO category specified in Column 5 of the row If the entry in the DB_Object_Symbol contains an underscore _ then the portion of the entry before the underscore will also be annotated as belonging to the GO categor
30. ar Profile 41 a Profile 41 SEE Profile 41 0 1 2 3 4 Profile 41 0 1 2 3 4 4 ror the Change v i v 0 86 0 Genes Assigned 31 8 Genes Expected p value 0 00 significant 4 way Change 86 0 Genes Assigned 31 8 Genes Expected p value 0 00 significant 8 0 of the 97 0 genes assigned to Profile 33 in the comparison experiment were also assigned to this profile p value 7e 8 0 of the 97 0 genes assigned to Profile 33 in the comparison experiment were also assigned to this profile p value 7e 9 Figure 35 On the left is an example of a model profile window that appears when a model profile box to the right of a yellow bar is pressed On the right is the same window after the button Click to plot only genes in intersection is pressed As mentioned in Section 4 3 a user can reorder the profiles on the model profile overview screen based on gene enrichment for a user defined set After the Compare button on the comparison dialog has been pressed the user defined gene set can be defined based on sets of genes assigned to profile s in the other data set This feature thus allows a user to visualize how a set of genes which all had the same expression profile s in one experiment responded in another experiment under different conditions On the left of Figure 36 is the window to define a gene set by which to reorder the original data set model profiles notice that the field Profile ID in Comp
31. arison Set is active On the right of Figure 36 is the window to define a gene set by which to reorder the comparison data set model profiles notice the field Profile ID in Original Set is active Pressing the Select button selects those genes from the other experiment assigned to the profile of the ID displayed Note that one can select genes from multiple profiles since selecting an additional profile ID does not clear any currently selected genes To create a gene set based on all the genes filtered in the other experiment set the profile ID value to 1 and then press select genes 40 Define Gene Set Sele Define Gene Set Sele Gene Name In Gene Sety We Gene Name In Gene Sety BTG2 200RF16 200RF18 4A ANXAS ARP LCN OX A2 BA CL4 LDN14 LDN4 FFA PYSL2 CE1 ROIL PR1 UT4 NA15 L23A L2RG 620 NID ABPS5 GF18 LJ20920 LJ23311 LJ90586 z ao CC SA CARP CLEN o COXA o CRY s CxCLI o DDB S DEFA DPYSL S EL o FABP5 S FGF18 S EHe FLJ20920 S FLI23311 o FLJ90586 o GATM S GSA o HPCL2 Y Profile ID in Comparison Set gH Select Genes Profile ID in Original Set 41 Select Genes Query Gene Set amp Load Gene Set Save Gene Set Query Gene Set Load Gene Set Save Gene Set Figure 36 Dialog windows to define gene sets The dialog window on the left is used to define a gene set to reorder model profiles from the original data set while the dialog on the
32. ayed the cluster means are on the same scale as the genes Average log of expression change ratio over time of genes in the cluster Lower left hand carner contains information relevant to the current reordering of clusters f ordering by number of genes this will be the number of genes assigned to the cluster f ordering based on a GO category or query set enrichment then this will be the number of genes in the selected GO category or set and assigned to this cluster then a semicolon and then the uncorrected p value for the enrichment Figure 39 Legend for a K means cluster box 44 Interface Options Gene display policy on main interface O Do not display O Display only selected Display all Change Color of Genes Y axis scale for genes on K means main interface should be O Cluster specific Global Scale should be based on only selected genes Y axis scale on cluster details windows should be O Determined automaticaly Fixed with parameters below Min aH Max JH Tick interval H X axis scale should be Uniform C Based on real time Figure 40 Above is the inteface options window similar to as in Figure 21 except the Y axis scale can only be Cluster specific or Global Category Name Min p value actual size DNA replication DNA metabolism cell cycle regulation of progression through cell cycle _ 3 1E 9 regulation of cell cycle 3 3E 9 nucleobase nucleoside nucleotide and n
33. c Bottom left Main interface displaying all individual gene expression profiles with the y axis scale set to Global Top right Main interface displaying all individual gene expression profiles with the y axis scale set to Profile Bottom right Main interface with a gene display policy of Display only Selected and when ordering by the GO category cell cycle The only gene expression profiles displayed correspond to GO cell cycle genes Zi AILSTEM Profiles 1 Clusters ordered based on number of genes and profiles ordered by significance default SSSA See MNAONA SNUS HNM MNA ANMMSN MMiika WWAN Figure 23 The main interface as in Figure 11 except the x axis time points are display proportional to the real sampling rate instead of uniformly 28 4 6 Zooming and Panning AILSTEM Profiles 1 Profiles ordered based on the actual size based ISMN Figure 24 The above image shows a screen shot of the profile overview interface zoomed in on the four profiles most enriched for cell cycle As Figure illustrates the model profile overview interface is zoomable To zoom in hold down the right mouse button and move the mouse to the right To zoom out hold down the right mouse button and move the mouse to the left To pan hold down the left mouse button while not over a model profile box and then move the mouse in the desired direction The ability to zoom in and out is powered by the the Piccolo Toolki
34. column The sample data in this figure and throughout the manual comes from p27 1 txt Seles SPOT Figure 3 A sample input data file displayed in a table after the button View Data File on the input interface was pressed Spot IDs included in the data file on the input interface must be checked otherwise the field must be unchecked The next column or the first column if spot IDs are not included in the data file contain gene symbols If a gene symbol is not available then the field can be left empty or a 0 can be placed in it Both the spot ID field and the gene symbol field may contain multiple entries delimited by a semicolon pipe or comma The sub entries in the field are only relevant in the context of gene annotations described in the next section The remaining columns contain the expression value at each time point ordered sequentially based on time If an expression value is missing then the field should be left empty The first row of the data file contains column headers and each row below the column header corresponds to a spot on the microarray If it is desired that the x axis be scaled proportional to the actual sampling rate then each column header must contain the time at which the experiment was sampled in the same units Each column must be delimited by a tab The tab delimited input data file should be an ASCII text file or a GNU zip file of an ASCII text file A tab del
35. d in the data file Using this file thus allows one to filter genes from the data by a criteria not implemented in STEM by excluding them from the data file but still include the filtered genes as part of the base set of genes during a GO enrichment analysis If genes appear in both Pre filtered Gene File file and the data file then the gene will only be added to the base set once The format of this file is the same as a data file except including the time series expression values is optional and if included they will be ignored As with a data file if the field Spot IDs included in the data file is checked then the first column will contain spot IDs and the second column will contain gene symbols otherwise the first column will contain gene symbols 3 3 2 Model Profile Options Advanced Options Filtering Model Profiles Clustering Profiles Gene Annotations GO Analysis s POR Maximum Correlation 1 Ee ma Maximum Number of Candidate Model Profiles 00 000 E Humber of Permutations per Gene 0 for all permutations soi E Significance Level oos H E Permutation Test Should Permute Time Point 0 E Correction Method Bonferroni False Discovery Rate O None E Figure 7 The above panel is used to specify options for selecting model profiles and assessing their statistical significance The panel used to adjust parameters related to model profiles appears
36. d p value is computed based on a randomization test where random samples of the same size of the set being analyzed is drawn The number of samples is specified by the parameter Number of samples for multiple hypothesis correction The corrected p value for a p value r is the proportion of random samples for which there is enrichment for any GO category with a p value less than r A Bonferroni correction is faster but a randomization test leads to lower p values 4 Model Profiles Overview Interface After the STEM clustering algorithm executes the model profile overview interface appears An example of such an interface is shown in Figure Each box corresponds to a different model temporal expression profile The number in the top left hand corner of a profile box is the model profile ID number If the box is colored then a statistically significant number of genes were assigned to the model expression profile Model profiles with the same color belong to the same cluster of profiles Clicking on a model profile opens a new window that provides more detailed information about the model profile and also the option to display gene tables and GO enrichment analysis tables The window that appears with details about a model profile is discussed in depth in Section 5 Along the bottom of the screen are several buttons Filtered Gene List Main Gene Table Interface Options Order Profiles By Order Clusters By Compare and a help icon The Filtered
37. del profile This is valid since the correlation coefficient is used to measure distance and is unaffected by scaling see Figure 22 top left If Profile specific is selected then the y scale of all genes in a profile box are on the same scale but the y scale in different profile boxes will be different see Figure 22 top right If Global is selected then all genes are plotted on the same y scale on the main interface See Figure bottom left Note that if there is one outlier gene and Profile specific is selected then the other genes in the profile of the outlier will look flat and if Global is selected all other genes will look flat If the gene display policy is to Display only selected and Profile specific or Global is selected then there is the further option to re adjust the y scale based on only the currently visible genes by selecting Scale should be based on only selected genes Note that the model profiles will generally be on different scales than the genes The options in this third section determine the y axis scale on the profile detail windows which appear when clicking on a profile box on the main interface If Determined automatically is selected then STEM automatically determines the y scale based on the expression level of the genes assigned to the profile The y scale may be different for each profile window If the option Fixed with parameters below is selected then the y scale on the profile windows will have a minimum and maxim
38. e button and the Profile Intersect GO Table buttons The Profile Intersect Gene Table button displays a gene table Section 5 1 of genes assigned to this profile which were also assigned to the profile to the left of the yellow bar in the other experiment that is the genes in the intersection The Profile Intersect GO Table buttons displays a table Section 5 2 with a gene enrichment analysis for genes in the intersection set Clicking on a profile to the left of the yellow bar opens a window which displays information about the profile but does not provide any information about gene intersections Correlation between profile 38 and 13 genes assigned to profile genes of the 277 assigned to profile 38 in the 38 in the first experiment first experiment that were also assigned to profile 13 in the second experiment p value for the of genes in the intersection Figure 34 A legend for the comparison interface The bottom left corner of profile boxes to the left of the yellow bar contain the number of genes assigned to the profile The bottom left corner of profile boxes to the right of the yellow bar contains the number of genes assigned to the profile that were also assigned to the profile to the immediate left of the yellow bar and then separated by a semicolon the p value for seeing this many or more genes in the intersection The upper right hand corner of the profile boxes to the right of the yellow bar contains the correlation wit
39. e parameter value will influence the clustering of model profiles Similarly if the Minimum Correlation Percentile parameter is set to 0 then only the Minimum Correlation parameter value will influence the clustering of model profiles 12 3 3 4 Gene Annotations Options Advanced Options Filtering Model Profiles Clustering Profiles Gene Annotations GO Analysis Only include annotations of type r Biological Process r Molecular Function v Cellular Component E Only include annotations with these taxon IDs E Exclude annotations with these evidence codes E Category ID mapping file Browse m Figure 9 The above panel is used to specify options related to gene annotations On the fourth panel shown in Figure 9 a user may specify options related to gene annotations The first three options allow one to filter annotations when the annotation file is in the official 15 column format The last field the Category ID mapping file is useful in the case in which genes are annotated as belonging to a category outside the Gene Ontology The options on this panel are as follows e Only include annotations of type Biological Process Molecular Function Cellular Component These three checkboxes allow one to filter annotations that are not of the types checked These three checkboxes only apply if the annotations are in the official 15 column GO format in which case the annotation type
40. er The first two columns of this table are the category ID and category name The third column contains the minimum p value of the gene enrichment of genes for that category for any profile computed based on the profile s actual size The fourth column also contains the minimum p value of the gene enrichment of genes for that category for any profile but computed based on a profile s expected size The actual size of a profile is the number of genes assigned to the profile The expected size is the number of genes expected to be assigned to the profile as computed based on a permutation test During a permutation test the order of the time point values before transformation Log normalize data Normalize data or No normalization add 0 are randomly permuted the transformation is applied and then genes are assigned to model profiles This is done for a large number of permutations and the expected number of genes assigned to a profile is the average number of genes assigned over all permutations The actual size based p value gene enrichment is computed based on a hypergeometric distribution Suppose there are a total of N genes on the microarray m of the these genes are in the category of interest v of the genes belong to the category of interest and were also assigned to the profile of the interest and the number of gene s assigned to the profile is s then the p value of seeing v or more genes belonging
41. erful Approach to Multiple Testing J Roy Stat Soc B MET 57 1 289 300 1995 Ernst J Nau G Bar Joseph Z Clustering Short Time series Gene Expression Data Bioinformatics Pro ceedings of ISMB 2005 21 Suppl 1 pp i1159 i168 2005 Gene Ontology tool for the unification of biology The Gene Ontology Consortium Nature Genet 25 25 29 2000 Guillemin K Salma N R Tompkins L S and Falkow S Cag pathogenicity island specific responses of gastric epithelial cells to Helicobacter pylori infection PNAS 99 15136 15141 2002 4T A Defaults File Format As mentioned in the preliminary section the default settings for STEM can be specified in a file and used through the d on the command line Below is a sample file The parameters names are on the left side and a tab separates them from their value Lines which begin with a are comments and are ignored Main Input Data_File data txt Gene_Annotation_Source Human EBI Gene_Annotation_File Cross_Reference_Source Human EBI Cross_Reference_File Clustering Method STEM Clustering Method K means STEM Clustering Method Maximum_Number_of_Model_Profiles 50 Maximum_Unit_Change_in_Model_Profiles_between_Time_Points 2 Number_of_Clusters_K 10 Number_of_Random_Starts 20 Normalize_Data Log normalize data Normalize data No normalization add 0 Normalize data Spot_IDs_included_in_the_data_file true Repeat Data Repeat_Data_Files comma delimited list Repeat_
42. esis correction This parameter specifies the number of random samples that should be made when computing multiple hypothesis corrected enrichment p values by a randomization test A randomization test is used when the p value enrichment is based on the actual size of the set of genes and Randomization is selected next to the Multiple hypothesis correction method for actual sized based enrichment label The Bonferroni correction is always used when the p value enrichment is based on the expected size of the set of genes The difference between actual and expected size enrichment is discussed in Section 4 3 Increasing this parameter will lead to more accurate corrected p values for the randomization test but will also lead to longer execution time to compute the values e Multiple hypothesis correction method for actual sized based enrichment This parameter controls the correction method for actual size based GO enrichment Expected size based p values are always corrected using a Bonferroni correction See Section 4 3 for a discussion on the differences between actual and expected size enrichment analysis The parameter value can either be Bonferroni or Randomization If Bonferroni is selected then a Bonferroni correction is applied where the uncorrected p value is divided by the number of categories meeting the minimum Minimum GO level and Minimum number of genes constraints If Randomization is selected the correcte
43. files Order Clusters and then Profiles by ME Category ID Category Name Min p value GO 0007049 cell cycle 3 2E 12 GO 0006259 DNA metabolism 3 4E 10 Go 0000074 regulation of progression through cell cycle 4 4 7E 10 GO 0051 726 regulation of cell cycle 4 9E 10 GO 0006260 DNA replication 1 4E 9 GO 0006139 nucleobase nucleoside nucleotide and nucleic 6 9E 9 GO 0006261 DNA dependent DNA replication 2 1E 8 GO 0005634 nucleus 2 4E 8 GO 0006281 DNA repair 2 0E 7 GO 0050875 cellular physiological process 2 4E GO 0043283 biopolymer metabolism 3 5E 7 GO 0044238 primary metabolism 5 2E 7 G0 0006974 response to DNA damage stimulus 5 6E 7 GO 0044424 intracellular part 9 0E 7 GO 0044464 cell part 9 4E GO 0009719 response to endogenous stimulus 9 5E GO 0005622 intracellular 1 5E 6 GO 0043231 intracellular membrane bound organelle 2 3E 6 GO 0043227 imembrane bound organelle 12 3E 6 Default Order Define Gene Set B Copy Table Save Table J Figure 19 The dialog box through which the ordering of cluster of profiles can be changed EA E 1 SER Clusters and then profiles ordered based onthe actual size based p value of gene enrichment of GO 00
44. h parameters t and DOE The most significant profiles appear to the left on the top row When profiles are reordered based on this The p value is computed as option the profile significance p value of a profile will appear in the bottom left hand corner of its profile box e Number of Genes Reorders profiles based on the number of genes assigned to the profile The profiles with the most genes assigned appearing to the left on the top row bottom left Figure 17p When profiles are reordered based on the number of genes assigned to the profile the number of genes assigned to a profile appears in the bottom left hand corner of its profile box e Expected Number Reorders profiles based on the expected number of genes assigned to the profile The expected number is computed based on a permutation test of the time points bottom right Figure 17 The profiles with the greatest expected number genes assigned appear to the left on the top row When profiles are reordered based on the expected number of genes assigned to the profile the expected number of genes assigned to a profile appear in the bottom left hand corner of its profile box e Default Order Reorders the profile back to their original order In the original default ordering all significant profiles appear before non significant profiles Profiles belonging to the same cluster are grouped together Clusters are ordered based o
45. h the profile to the left of the yellow bar On the bottom of the comparison window are four yellow buttons which are used to rearrange the profile boxes on the main window These buttons function as follows e Swap Rows and Columns Interchanges which data set is to the left of the yellow bar and which is to the right of the yellow bar e Order By Profile ID This button returns the profile pairs to their default ordering By default the profiles to the left of the yellow are first ordered by increasing ID Profiles to the right of the yellow bar are then ordered within the row by increasing ID e Order By Significance This reorders profile pairs based on statistical significance of the gene set intersec tion In any row the profiles to the right of the yellow bar are ordered with increasing p value for the gene set intersection with the profile to the left of the yellow bar The profiles to the left of the yellow bar are ordered to have increasing minimum intersection p value significance with a profile in its row to the right of the yellow bar e Order By Correlation This reorders profile pairs based on correlation In any row the profiles to the right of the yellow bar are ordered based on increasing correlation with the profile to the left of the yellow bar 39 The profiles to the left of the yellow bar are ordered to have increasing minimum correlation with a profile in its row to the right of the yellow b
46. he profile being analyzed that were also annotated as being cell cycle genes 36 6 Comparison Compare Comparison Data File PAI tt amp Browse View Comparison Data File Maximum uncorrected intersection p value 0 005 Minimum number of genes in intersection Ja Figure 32 The comparison dialog box which is used to specify a comparison data set and parameters for gene set intersections of interest Pressing the Compare opens two new windows one is a model profile overview for the comparison data set and the other is the main comparison window STEM facilitates the comparison of gene expression data sets from two different experimental conditions and in particular allows automatic identification of statistically significant sets of genes which are co expressed under both experimental conditions STEM can automatically identify pairs of model profiles one from each experiment for which the intersection of the set genes assigned to the two profiles is statistically significant Suppose there are N genes on the microarray n genes are assigned to a profile in the first experiment n genes assigned to a profile 7 in the second experiment and a total of t genes are in the intersection of the set of genes assigned to profile in the first experiment and profile j in the second experiment then the p value of seeing t are more genes in the intersection is computed based on the hypergeometric distributi
47. he query set that are assigned to any profile that is part of the profile s cluster of profiles If the profile window was opened by clicking on a row in the main gene table as described in Section 4 1 then a button will appear to plot only the gene of the row that was clicked on This is the Click to plot only gene STAM2 button on the left side of Figure Once the button is pressed the button will be replaced with the ol Profile 9 Profile 9 Profile 9 0 1 2 3 4 Profile 9 0 1 2 3 4 130 0 Genes Assigned 34 7 Genes Expected p value 0 00 significant 3 mato Change 130 0 Genes Assigned 34 7 Genes Expected p value 0 00 significant GO 0007049 cell cycle GO 0007049 cell cycle 3 Expression Change v v 0 Profile actual size based enrichment uncorrected p value 4 8E 11 18 0 130 0 vs 387 20452 15 5 genes Profile actual size based enrichment uncorrected p value 4 8E 11 18 0 130 0 vs 387 20452 15 5 genes Figure 26 The window on left is an example of a model profile detailed information window that appears when the profiles are sorted based on enrichment for a GO category in this case the cell cycle The window on right is the same window after a user clicks Click to plot only profile cell cycle genes Pressing the Profile cell cycle Gene Table displays a table of genes assigned to the profile that are also cell cycle genes Click to plot all profile genes button right side of F igure
48. imited text file can easily be generated in Microsoft Excel by choosing Text Tab delimited as the Save as type type under the Save As menu To view the contents of the data file from the interface press the button View Data File and then a table such as in Figure 3 will appear Before gene expression time series are matched against model temporal expression profiles the time series must be transformed to start at 0 The transformation that is used to do this can be selected to be of one of three types Log normalize data Normalize data or No normalization add 0 Given a time series vector of gene expression values vo U1 V2 Un the transformations are as follows e Log normalize data transforms the vector to 0 loga 54 log2 54 1082072 e Normalize data transforms the vector to 0 v1 Vo V2 Vo Un Vo e No normalization add 0 transforms the vector to 0 vo U1 Va Un It is recommended that after transformation a time series represent the log ratios of the gene expression levels versus the level at time point 0 Time point 0 usually corresponds to a control before the experimental conditions were applied If the input data file contains raw expression values as from an Oligonucleotide array then the Log normalize data option should be selected If any values are 0 or negative and the Log normalize data option is selected then these values will be treated as missing
49. in Figure The parameters on this panel are only relevant to the STEM clustering method and not K means clustering The first two parameters Maximum Correlation and Maximum Number of Candidate Model Profiles influence the selection of model profiles along with the two parameters from the main input interface Maximum Number of Model Profiles and Maximum Unit Change in Model Profiles between Time Points The final three parameters Number of Permutations per Gene Significance Level and Correction Method are related to the statistical test of whether a profile has a statistically significant number of genes assigned The parameters on this panel are described below e Maximum Correlation This parameter specifies the value that the maximum correlation between any two model profiles must be below and thus can be used to guarantee that two very similar profiles will not be selected Lowering this parameter could have the effect that the number of model profiles selected is less than the Maximum Number of Model Profiles even if more candidate model profiles are available 10 This parameter s maximum value is 1 thus preventing two perfectly correlated model profiles from being selected Maximum Number of Candidate Model Profiles Candidate model profiles are non constant profiles which start at 0 and increase or decrease an integral number of units that is less than or equal to the value of the Maximum Unit Change in Model P
50. ion profile Colored profiles have a statistically significant number of genes assigned Clicking on a profile box display detailed information about the profile The profiles and cluster of profiles can be reordered by various criteria by pressing Order Profiles By or Order Clusters By with additional help information The last subsection of this section Section 4 6 describes how one can zoom in or out on any portion of the main window 4 1 Main Gene Table Pressing the Main Gene Table button displays a table which has a row corresponding to every gene that was not filtered and thus assigned to a model profile The table includes the gene s expression values after transformation and the profile s to which the gene was assigned An example of such a table is shown in Figure 13 Clicking on a row of the table opens a new window containing detailed information about the profile to which the gene of the row was assigned This new window is described in Section 5 An option will also appear on the newly opened window to plot only the expression of the gene of the selected row The columns of the table are as follows e Selected An entry in this column contains a Yes if the gene of the row is part of a category or gene set by which the profiles are ordered otherwise the field is empty e Gene Symbol This column contains the gene symbols The name for this column is read from the header in the data file e Spot
51. l in the case that the naming convention used for genes in the data file is different than what is used in the gene annotation file A cross reference file establishes that two or more symbols refer to the same gene Note that the cross references is only used to map between gene symbols and not spot IDs and gene symbols The Cross Reference Source field gives the option to select either User Provided No cross references or cross references for Arabidopsis Chicken Cow Human Mouse Rat or Zebrafish provided by the European Bioinformatics Institute EBI If User Provided is selected for the cross reference file field then the Cross Reference File field becomes editable and a user can specify a cross reference file Any gene symbols listed on the same line in the cross reference file will be considered equivalent The symbols on a line can be delimited by either a tab semicolon comma or a pipe As with gene annotations files a cross reference file can either be in an ASCII text file or GNU zip version of an ASCII text file At the bottom of the gene annotation section of the interface is the phrase Download the latest and then three checkboxes Annotations Cross References and Ontology If the Annotations box is checked then the file listed in the Gene Annotation File box will be downloaded from ftp ftp geneontology org go gene associations unless it is an EBI data source
52. ll evidence codes are assumed to be acceptable Evidence code symbols are IEA IC IDA IEP IGI IMP IPI ISS RCA NAS ND TAS and NR Information about GO evidence codes can be found at Note that this field only applies if the gene annotations are in the official 15 column GO annotation format The evidence code is the entry in column 13 7 For example to exclude the annotations that were inferred from electronic annotation or a non traceable author statement the field should contain EA NAS e Category ID mapping file This file which is optional specifies a mapping between gene category IDs and category names for categories which are not official Gene Ontology categories The mapping between IDs and names for official GO categories are defined in the file gene_ontology obo If a category ID appears in the gene annotation file but does not correspond to an official Gene Ontology category and is not defined in a Category ID mapping file then the category ID is used in place of the category name A category ID mapping file has two columns delimited by a tab The first column contains category IDs and the second column contains category names Each line defines a mapping between one category ID and names Below is a short sample file ID_A CategoryNameA ID_B CategoryNameB ID_C CategoryNameC 3 3 5 GO Analysis Options The final advanced options panel shown in Figure 10 controls options related to Gene Ontology GO enrich
53. ment 2 Advanced Options Filtering Model Profiles Clustering Profiles Gene Annotations GO Analysis Minimum GO level J H Minimum number of genes aa E Number of samples for randomized multiple hypothesis correction soo E Multiple hypothesis correction method for actual size based enrichment Bonferroni Randomization E Figure 10 The above panel is used to specify options for the Gene Ontology enrichment analysis analysis Note that categories that appear in a gene annotation file even if not part of the official Gene Ontology are also included in a GO analysis The parameters included on this panel are as follows e Minimum GO level Any GO category whose level in the GO hierarchy is below this parameter will not be included in the GO analysis The categories Biological Process Molecular Function and Cellular Component are defined to be at level 1 in the hierarchy The level of any other term is the length of the longest path to one of these three GO terms in terms of the number of categories on the path This parameter thus allows one to exclude the most general GO categories e Minimum number of genes For a category to be listed in a gene enrichment analysis table described in Section 5 2 the number of genes in the set being analyzed that also belong to the category must be greater than or equal to this parameter 14 e Number of samples for randomized multiple hypoth
54. method for actual size based enrichment then the corrected p value is computed based on a Bonferroni correction See section 3 3 5 for a discussion on these two methods for correcting GO enrichment p values A gene enrichment table can be sorted by any column in ascending or descending order by clicking on the column header The contents of the table can also be saved to a text file using the Save Table button or copied to the clipboard using the Copy Table button Clicking on a row of the gene enrichment table will display a gene table that only includes genes that belong to category of the row and also the set being analyzed For example if a user clicked on the cell cycle row a table such as that in Figure 31 will appear which contains only genes that were assigned to the profile being analyzed that were also annotated as being cell cycle genes Weight Gene Symbol SPOT 1 00 MCME 1310 1 7642 1 00 CDK 2845 19180 1 00 MCMS5 2856 14160 16303 1 00 MCM3 3790 1 00 DKC1 8671 1 00 PCNA 9116 17976 1 00 GMNN 11127 15614 1 00 EEF1E1 12291 1 00 _ NME1 12422 1 00 ZAINT 17169 1 00 CDC6 18173 1 00 AIF 1 18414 1 00 cDC20 18956 B Copy Table Save Table B Copy Gene Names Save Gene Names Figure 31 A table that appears after clicking on the cell cycle row in the gene enrichment table The table only includes genes that were assigned to t
55. ming the user selects the STEM Clus tering Method then two options related to selecting temporal model expression profiles appear directly on the main input interface window These options are e Maximum Number of Model Profiles This parameter specifies the maximum number of model profiles that can be selected Model profiles are selected from a larger set of candidate model profiles Candidate model profiles are non constant profiles which start at 0 and increase or decrease an integral number of units that is less than or equal to the value of the Maximum Unit Change in Model Profiles between Time Points See for a discussion on how a set of distinct and representative set of model profiles are selected from the larger set of candidate model profiles If the value of Maximum Number of Model Profiles is set to 0 then there is no hard upper bound on the number of model profiles and the number of model profiles is limited only by the number of candidate profiles and the Maximum Correlation parameter under the Model Profiles section of Advanced Options e Maximum Unit Change in Model Profiles between Time Points This parameter specifies the maximum number of a units a model profile may change between time points A model profile between two consecutive time points can either stay constant or increase or decrease an integral number of units up to this parameter value If a user selects K means clustering then these two options do
56. mization Interface Options Gene_display_policy_on_main_interface Do not display Display only selected Display all Do not display Gene_Color R G B 204 51 0 Y axis_scale_for_genes_on_main_interface_should_be Gene specific Profile specific Global Profile specific Y axis_scale_for_genes_on_k means_main_interface_should_be Cluster specific Global Global Scale_should_be_based_on_only_selected_genes true Y axis_scale_on_details_windows_should_be Determined automatically Fixed Determined automatically Y_scale_min 3 Y_scale_max 3 Tick_interval 1 X axis_scale_should_be Uniform Based on real time Uniform 49 B Using STEM for Standard Gene Ontology Enrichment Analysis STEM may be used for standard Gene Ontology enrichment analysis for non time series data in two ways Given a data file of genes with a single time point column STEM will perform a Gene Ontology enrichment analysis for those genes whose absolute value exceeds the value specified by the Minimum Absolute Expression Change parameter In this case the base set of genes is all genes in the data file STEM can also be used to do an enrichment analysis for an arbitrary set of genes and an arbitrary base set of genes The set of genes to do an enrichment analysis on is specified in the Data File while the base set of genes are specified in the Pre filtered Gene File The first line of these files is a header line and every line below the header line will contain one gene pe
57. n the total number of genes assigned to any profile in the cluster Within clusters of profiles and among non significant profile the profiles are ordered based on increasing p value for the significance of the number of genes assigned versus what was expected e Define Gene Set Pressing the Define Gene Set brings up a dialog box Figure 18 which allows one to reorder profiles by enrichment for genes in a user defined gene set Any gene which is checked will be included in the gene set The button Unselect All unselects all genes in the set while the button Select All selects all genes A gene set can be loaded from a text file by pressing Load Gene Set and then specifying the name of the file containing the gene names One gene name should appear on each line of the file and there should be no header lines in a file Pressing Save Gene Set exports the current selected genes to a text file Pressing the button Query Set reorders the model profiles based on p value gene enrichments for genes in the query set As with GO categories the enrichment can be computed based on either the actual size or expected size of the profile depending upon which is selected in the Order Profiles By window The set of genes can also be selected to be the set of genes assigned to a profile in comparison data set as is explained in Section 6 21 AILSTEM Profiles 1 E imj X Profiles ordered based on profile ID BM wii M MAAN VINIMWN SMI
58. nelle 2436 cellular metabolism 3121 nucleotidyltransferase activity 62 metabolism 3326 intracellular organelle 2795 phosphoinositide mediated signaling 45 cell part 4574 transferase activity t99 3 4E 10 4 7E 10 4 9E 10 1 4E 9 5 9E 9 2 1E 8 2 4E 8 2 0E 7 2 4E 7 3 5E 7 5 2E 7 5 6E 7 9 0E 7 9 5E 7 1 5E 6 2 3E 6 2 3E 6 2 3E 6 2 7E 6 4 6E 6 7 4E 6 9 6E 6 2 4E 5 2 4E 5 0 001 0 001 0 001 lt 0 001 0 001 0 001 0 001 0 001 0 001 0 001 0 001 0 001 0 001 0 001 0 001 0 001 0 001 0 001 0 001 0 001 0 001 0 001 0 001 0 001 13 9 13 2 13 2 9 3 20 7 67 20 6 8 1 25 7 17 0 22 5 8 0 22 4 8 0 22 2 19 5 19 5 21 2 5 6 20 9 19 2 47 20 9 11 2 330 288 289 16 0 15 0 15 0 110 0 30 0 7 0 31 0 9 0 53 0 25 0 42 0 9 0 43 0 9 0 44 0 35 0 35 0 41 0 6 0 42 0 37 0 5 0 50 0 16 0 GO 0016740 Click for GO Results Based on the Profile s Expected Size B Copy Table Save Table Figure 30 A gene enrichment analysis table Clicking on a row of the table brings up a gene table that includes only the genes annotated as belonging to the category of the row that are also in the set being analyzed The above table is enrichment based on the actual size of the profile Clicking
59. nge is defined in the context of gene filter If Mazximum Minimum option is selected a gene will be filtered if the maximum absolute difference between the values of any two time points not necessarily consecutive after transfor mation is less than the value of the Minimum Absolute Expression Change parameter If Difference from 0 is selected a gene will be filtered if the absolute expression change from time point 0 at all time points is less than the value of the Minimum Absolute Expression Change parameter Formally suppose 0 v1 V2 Un is the expression level of a gene after transformation and let C be the value of the Minimum Absolute Expression Change Ifthe Maximum Minimum option is selected a gene will be filtered if max 0 v1 v2 Un min 0 V1 V2 Un lt C If the Minimum Absolute Expression Change option is selected the gene will be filtered if max 0 v1 val Un lt C Only the Mazimum Minimum option guarantees that the same set of genes would be filtered for any permutation of the time points For the Difference from 0 this is in general not true in this case the permutation test is based on the set of genes passing filter under the original order of time points o Pre filtered Gene File This file is optional If included any genes listed in the file will be considered part of the initial base set of genes during a Gene Ontology GO enrichment analysis in addition to any genes include
60. not appear and instead two options specific to K means clustering appear see Section 7 The remaining options can be accessed by pressing the Advanced Options button These remaining options are divided into five panels Filtering Figure 6 Model Profiles Figure Clustering Profiles Figure 8 Gene Annotations Figure 9 and GO Analysis Figure 10 which are discussed in the next subsections 3 3 1 Filtering Options Through the parameters on the Filtering panel shown in Figure 6 a user can adjust the criteria STEM uses to filter genes If a gene is filtered then it will be excluded from further analysis Genes can be filtered if they do not show a sufficient response to experimental conditions Minimum Absolute Expression Change there are too many missing values Maximum Number of Missing Values or the gene expression pattern over repeats is too inconsistent Minimum Correlation between Repeats If the Log normalize data or Normalize data options are Advanced Options Filtering Model Profiles Clustering Profiles Gene Annotations GO Analysis Maximum Humber of Missing Values J fal Minimum Correlation between Repeats j m Minimum Absolute Expression Change H Change should be based on Maxzimum Minimum Difference from 0 E Pre fittered Gene File Browse m Figure 6 The above panel is used to specify gene filtering options selected a gene
61. notation Info Gene Annotation Source Human EBI l Cross Reference Source Human EBI Gene Annotation File gene_association goa_human gz Browse Cross Reference File humanxrefs gz Browse Download the latest _ Annotations Cross References _ Ontology 3 Options Clustering Method STEM Clustering Method Y Maximum Number of Model Profiles 50 Maximum Unit Change in Model Profiles between Time Points 2 S 2004 Carnegie Mellon University All Rights Reserved P Figure 1 Above is the main input interface which is the first screen that appears when STEM is launched From this screen a user specifies the input data gene annotation information and various execution options Pressing the execute button at the bottom of the interface causes the clustering and gene enrichment analysis algorithms to execute and then a new interface described in Section 4 to appear in Section 4 If the data file does not have two or more time points then results for a standard gene enrichment analysis will be displayed For details about using STEM for standard gene enrichment analysis on non time series data consult Appendix B 3 1 Expression Data Info The first field in the expression data section of the interface is the Data File field where a user specifies the input data file An input data file consists of gene symbols time series expression values and optionally spot I
62. o parameters specify the number of clusters and the number of random starts Similarly one can open a table with GO analysis results for the set of genes assigned to the cluster as one could do for all genes assigned to a profile described in Section 5 2 The GO analysis can only be based on the actual size of the cluster since there is no notion of the expect sized of a K means cluster Pressing the Main Gene Table on the main K means interface is the same as described in Section 4 1 for the STEM clustering method except the table has the cluster the gene was assigned to instead of the profile The Filter Gene Table is identical to that described in Section 4 2 Comparison for AK means works the same way as described in Section 6 except STEM profiles are replaced with K means clusters Figure 43 shows the comparison legend for the comparison interface with K means analogous to Figure 34 for comparison with STEM profiles 43 All K Means Clusters 1 Sc All K Means Clusters 1 Clusters ordered based on cluster ID Clusters ordered based on cluster ID SHES Figure 38 Above is the main output interface which is similar to the interface described in Section 4 Each box corresponds to a K means cluster and displays the average expression of genes in the cluster Left No individual gene expression profiles are displayed Right The individual gene expression profiles are displayed on a Global scale When genes are displ
63. ofile cell cycle genes button on the left side of Figure 26 Once this button is pressed the button will be replaced with a button that says Click to plot all profile genes right side of Figure 26 which gives the user the option to revert back to having all the profile genes plotted If the profiles or cluster of profiles are ordered based on a user defined gene set referred to as a query gene set then there will be several additional buttons Figure 27 The button Click to plot only profile query set genes replots the window with only profile genes that also belong to the user defined gene set Pressing the button will cause the button to be replaced with a Click to plot all profile genes button which pressing will revert to the original window Above the Profile Gene Table and Profile GO Table are two buttons the Profile Query Gene Table and the Profile Query GO Table Pressing the Profile Query Gene Table displays a table with all genes assigned to the profile that also belong to the query gene set Pressing the Profile Query GO Table displays a gene enrichment table for just the genes assigned to the profile that are also part of the query set If the profile is part of a non singleton cluster of profiles then two additional buttons will appear the Cluster Query Gene Table and Cluster Query GO Table buttons These buttons are analogous to the Profile Query Gene Table and Profile Query GO Table buttons but are based on all genes in t
64. on displays a window shown in Figure similar to what was described in Section except in the options for y axis scale for genes on the main interface Profile specific has been replaced with the analogous Cluster specific option and there is no longer the Gene specific option When genes are displayed on the main profile the cluster means are plotted on the same scale as the genes Pressing the Order Cluster By button brings up the dialog box in Figure 41 through which the clusters can be reordered The reordering criteria of the clusters can be the number of genes assigned to the cluster or p value enrichment for a GO category or user defined gene set Pressing a cluster box opens a window such as Figure 42 with detailed information about a K means cluster similar to the model profile detailed interface described in Section 5 From this window one can open a table of all genes assigned to the cluster as one could do for all gene assigned to a STEM profile described in Section 5 1 42 STEM Short Time series Expression Miner mi i i H Cross References Ei Ontology sene Annotation File gene_association goa_human gz Figure 37 Above is the main input interface described previously in Section 3 with the clustering method set to K means Two parameters appear when K means is selected that do not appear when the STEM clustering method is selected These tw
65. on to be MIN ninj 23 A 2 5 To specify a comparison data set from the model profile overview screen press the Compare button Pressing this button will open a comparison dialog such as shown in Figure 32 A user can specify the name of comparison data file in the field Comparison Data File Note that STEM requires that the comparison data have the same number of time points as the original data Once a name of a file is specified to view the contents of the file specified in the Comparison Data File press the button View Comparison Data File Pressing the button Comparison Repeat Data will open a repeat dialog window from which to specify repeat data for the comparison experiment This dialog window appears in Figure 4 and was described back in Section 3 1 Below the Comparison Repeat Data button are two parameters e Maximum uncorrected intersection p value The maximum uncorrected intersection p value for the inter section to be of interest e Minimum number of genes in intersection The minimum number of genes in the intersection of the set of genes assigned to two profiles for the intersection to be of interest Pressing the yellow Compare button will launch two new windows One of the windows that is launched contains the model profile overview screen for the comparison data set This is the same interface that is described in Section The other window that appears is the main comparison window an ex
66. ontal labels will read Original Set Profiles A profile appears to the right of the yellow bar if the intersection of the set genes assigned to it and the profile to the immediate left of the yellow bar satisfy the size and p value constraints specified on the comparison dialog The legend that appears when a user presses the help icon information appears in Figure and explains what the various numbers mean on the profile boxes This window as with the main profile screen is zoomable and pannable Instructions for zooming and panning can be found in Section 4 6 Clicking on a profile box to the right of a yellow bar launches a detail model profile window that includes the option to obtain information about the genes in the intersection between the profile clicked on and the profile to the immediate left of the yellow bar left side Figure 35 Near the top of the window is a line of text indicating how many genes were in the intersection and the p value of the intersection The intersection profile window also contains a button which plots only those genes in the profile which were also assigned to the profile in its row to the left of the yellow bar in the other experiment After pressing the Click to plot only genes in intersection 38 one has the option to press the button Click to plot all profile genes to revert back to the original screen Two additional buttons that appear on the profile interface are the Profile Intersect Gene Tabl
67. r expected is also then computed Statistically significant model profiles which are similar to each other can be grouped together to form clusters of profiles The biological significance of the set of genes assigned to the same profile or the same cluster of profiles can then be assessed using a GO enrichment analysis For a more detailed discussion of the novel method STEM uses to cluster genes and associate statistical significance with genes having the same expression profile see 3 1 2 Manual Overview The remainder of the main portion of the manual contains six sections Section 2 contains instructions on installing and starting STEM Section 3 discusses the input to STEM including execution options and data file formats Section 4 describes the model profile overview interface which allows a user to visualize on a zoomable interface a large number of model profiles and order them based on their relevance to a GO category or user defined gene set Section 5 describes the interface for obtaining detail information about a model profile or cluster of profiles including a table of genes assigned and a table of GO category enrichments Section 6 describes STEM features to compare two data sets from different experimental conditions STEM also provides an implementation of the standard K means clustering algorithms which is described in Section 7 Sections are presented assuming a user is interested in the novel STEM cl
68. r line As with a data file the field Spot IDs included in the data file should be unchecked unless spot IDs are the first column and gene symbols are the second column in which case the field should be checked After pressing execute a gene enrichment analysis table will appear as described in Section 5 2 50 C Gene Annotation Sources The table below lists all gene annotation data sets that can be selected under Gene Annotation Source More information about these annotation data sets can be found here http www geneontology org GO current and for the EBI annotations here http www ebi ac uk GOA Subsets of the UniProt annotations for a large number of organisms provided by the European Bioninformatics Institute EBI can be found here http www ebi ac uk GOA proteomes html and can be used through the User Provided option under the Gene Annotation Source ol
69. repeat data files specified otherwise it is gray Repeat data files must have the same format as the original data file including the same number of rows and columns Repeat data values will be averaged with the values from the original data file using the median Repeat data can be selected to be from either Different time periods or The same time period If the data is from Different time periods then data was collected over multiple distinct time series but presumably at the same sampling rate If the data is from The same time period then this implies multiple measurements were collected at each time point during one time series If the repeat data is selected to be from the The same time period then the file to which any two column of values for the same time point belong could be interchanged without effect while if the repeat data is selected to be from Different time periods this is not the case If the repeat data is from Different time periods the repeat data will be averaged after normalization while if the repeat data is from The Same Time Period the repeat data will be averaged before normalization In the case the repeat data is from Different time periods the repeat data can be used to filter genes with inconsistent expression patterns and also to provide noise estimates by which to base clustering model profiles as explained in Section 3 3 3 2 Gene Annotation Info GO 0016491 GO 0000004 GO 0008372 2
70. right is used to define a gene set to reorder model profiles from the comparison data set Al T K means In addition to providing a novel clustering method designed for short time series expression data 3 STEM also provides an implementation of the standard K means algorithm for clustering To use the K means clustering algorithm in STEM select K means under Clustering Method Figure 37 The AK means clustering algorithm partitions genes into K sets S1 S2 Sx where K is an input parameter provided by a user in the field Number of Clusters K Each set S has a center c associated with it where the center represents the mean of all genes assigned to the set S After transformation described in Section 3 1 a gene x and center c are T 1 element vectors that can be written as 0 j1 2 U 7 and 0 Ci1 cia Cir respectively The K means algorithm attempts tries to minimize the function dy dy dy im im i 1 2 E S m 1 The K means algorithm starts with randomly selected centers where in STEM s implementation the initial centers are chosen to be randomly selected genes The algorithm then iterates between two steps until convergence In one step each gene is reassigned to the cluster of the center to which it is closest In the next step the center of each cluster is recomputed based on the new assignment of genes to clusters The algorithm terminates when no changes in reassignment can
71. rofiles However every window will contain a Profile Gene Table and Profile GO Table button The Profile Gene Table button displays a table with all the genes assigned to the profile A gene table is described in Section 5 1 The profile Profile GO Table brings up a table with gene category enrichments among genes assigned to the profile A gene category enrichment table is described in Section 5 2 If a profile is part of cluster of profiles which is not a singleton then two additional buttons will appear along the bottom row of the window the Cluster Gene Table and Cluster GO Table buttons The Cluster Gene Table button displays a gene table that includes all genes assigned to any profile in the cluster of profiles to which the profile belongs The Cluster GO Table button displays a gene enrichment table that is based on enrichment for all genes assigned to any profile that is part of its cluster of profiles If the profiles or cluster of profiles are reordered based on a category then two additional buttons will appear above the bottom row Pressing the top of these two button will display a table of the genes that were assigned to the profile and also belong to the category by which the profiles are ordered In Figure 26 this is the Profile cell cycle Gene Table button Below this button is a button which gives the option to plot only the profile genes belonging to the category by which the profiles are ordered This is the Click to plot only pr
72. rofiles between Time Points If the number of candidate model profiles exceeds this parameter then instead of explicitly generating all candidate model profiles a subset of candidate model profiles of this size will be randomly selected In most cases there will be no need to adjust this parameter Number of Permutations per Gene This parameter specifies the number of permutations of time points that should be randomly selected for each gene when computing the expected number of genes assigned to each of the model profiles If this parameter is 0 then all permutations are used Increasing the number of permutations will lead to slightly greater accuracy at the expense of greater execution time Significance Level The significance level at which the number of genes assigned to a model profile as compared to the expected number of genes assigned should be considered significant If the Correction Method parameter for multiple hypothesis testing is Bonferroni then this parameter is the significance level before applying a Bonferroni correction If Correction Method is False Discovery Rate then this parameter is the false discovery rate If Correction Method is none then this parameter is the uncorrected significance level Permutation Test Should Permute Time Point 0 If the box Permutation Test Should Permute Time Point 0 is checked then the permutation test permutes all time points including time point 0 when compu
73. set then an additional line of text will appear below the first two lines of text Figures 26 27 The additional line indicates the uncorrected p value of the profile gene enrichment for the category or gene set the profiles are being ordered by In parentheses are two ratios with a vs in between thus having the form 4 VS In first ratio the numerator A is the number of genes assigned to the profile that belong to the category or user defined gene set by which the profiles are ordered The second number B is either the total number of genes assigned to the profile if the profiles are ordered based on actual size gene enrichment or the expected number of genes assigned to the profile if the profiles are ordered based on expected size gene enrichment In the 29 Profile 43 SS Baie Profile 43 0 1 3 3 2 Profile 43 0 1 3 3 2 5 Mev Change 150 0 Genes Assigned 28 5 Genes Expected p value 4 0E 59 significant 5 a Change 150 0 Genes Assigned 28 5 Genes Expected p value 0 00 significant Profile 9 Profile 9 0 1 2 3 4 3 Expression Change 130 0 Genes Assigned 34 7 Genes Expected p value 0 00 significant amp v i v 0 Figure 25 Example of detailed model profile information windows The top two images are of the same profiles but the left image is with the x axis scaled to be based on real time and the y axis to be uniform The window plots
74. sing the Save Gene Names button or copy it to the clipboard with Copy Gene Names 4 2 Filtered Gene List Table of Genes Filtered Seles Selected Gene Symbol SPOT DS PT Taba 1868 SPOT BB BROT OF RT a BROT oo OAS o 2 ROT BROT 18398 o O SPOT 22036 AE I Copy Table Save Table Copy Gene Names Save Gene Names Figure 14 An example of a list of filtered genes If a user presses the button Filtered Gene List a table such as the table in Figure appears The table contains a list of genes that were filtered and thus not assigned to a model expression profile The parameters controlling filtering of genes are described in Section 3 3 1 The three columns of this table the Selected column the gene symbols column and the spot ID column are the same columns as the first three columns of the main gene table described in section 4 1 4 3 Ordering Profiles An important feature of STEM is its ability to easily reorder model profiles on the overview screen by a number criteria including the p value of gene enrichment for any Gene Ontology category or a user defined gene set To reorder the profiles first press the button Order Profiles By on the model profile overview interface A window such as the one in Figure 15 will then appear The top portion of the window contains a table The table contains 18 Ban Category Name Min p value Min p value actual size expected size cell cycle DNA metabolism
75. sing the button Interface Options After pressing the Interface Options button on the main interface an Interface Options window such as in Figure 21 appears This window is divided into four sections The options in the first section control the individual gene display policy on the main interface and the color of the genes if displayed If Do not display is selected then individual gene expression profiles are not shown on the main interface only the model profile If Display only selected is the selected option then indivdual gene expression profiles are only displayed when ordering the profiles or cluster of profiles by a GO category or gene set see Figure 22 bottom right In this case only genes which belong to the selected GO category or gene set by which the ordering is based is displayed on the main interface If Display all is selected then all genes not filtered are displayed see Figure 22 top left top right and bottom left If Display only selected or Display all is selected then there is the option to change the color of the genes on the main interface by pressing the Change 25 Color of Genes button The color of the text of this button will be the same color as the genes The options in the second section determines the y axis scale of the individual gene expression profiles dis played on the main interface If Gene specific is selected then each individual gene is scaled separately to be closely aligned with the mo
76. t 1 which is distributed under a BSD license 5 Model Profile Details Interface When a user clicks on a model profile box on the model profile overview screen of the software on a model profile box on the comparison interface screen discussed in Section 6 or on a row in the main gene table a window with detailed information about the profile and the genes assigned to the profile appears in a new window Figure 25 The window displays a graph of the expression values after transformation of all genes assigned to the profile Note that whether the time points on the x axis are uniformly spaced or based on real time is determined by the x axis scale setting under the Inteface Options windows as discussed in Section 4 5 Along the top center of the window are two lines of text The first line contains the model profile ID and a vector representing the expression pattern The second line of the window contains a count of the number of genes assigned to this model expression profile a count of the expected number of genes assigned to the model profile based on a permutation test the uncorrected p value for the significance for the number of genes assigned being greater than the number expected and whether or not this is statistically significant as defined by the parameters on the Model Profiles panel under Advanced Options If the profiles are reordered by gene enrichment for genes belonging to a GO category or a user defined gene
77. ting the expected number of genes assigned to a profile In this case STEM finds profiles with significantly more genes assigned than expected if all the input columns had been randomly reordered If this box is not checked the permutation test permutes all time points except for time point 0 In this case STEM finds profiles with more genes assigned than expected if all the columns except for the first column had been randomly reordered Note that if No normalization Add 0 was selected on the main input interface the column of added Os is considered the first input column Permuting time point 0 is generally preferred since only this test takes into account significant changes that occur between time point 0 and the immediate next time point However in some cases based on experimental design a gene s expression value before transformation at time point 0 is expected to be known more accurately than the other time points and because of this asymmetry as explained below not permuting time point 0 can also be useful The time point 0 expression value before transformation can be known more accurately than other time points in a two channel experiment where the time point 0 sample is used as the reference sample or in a single channel experiment where extra repeats were done for time point 0 In these experiments there is a lower variance in a gene s time point 0 expression value than at other time points One could thus expect
78. u 2 8E 8 cytoskeletal protein binding DNA dependent DNA replication nucleus cell proliferation collagen catabolism o nenez7o peptdogycan metabolism GO 0042254 ribosome biogenesis and assembly biopolymer metabolism mitotic cell cycle t 0P ale O ULALE Cluster ID Number of Genes Define Gene Set Copy Table Save Table Figure 41 Above is the window to order K means clusters Clusters can be ordered based on ID number of genes or relevance to a GO Category or user defined gene set 45 Cluster 7 DEK Cluster 7 0 0 0 9 0 8 0 7 0 8 Expression Change i 4 wwij v 0 548 0 Genes Assigned Figure 42 Above is an example of a window that provides detailed information about a K means cluster K means Cluster IDS Correlation between clusters 6 and 2 average expression values genes assigned to cluster genes of the 87 assigned to cluster 6 in the first 6 in the first experiment experiment that were also assigned to cluster 2 in the second experiment p value for the of genes In the intersection Figure 43 Legend for the comparison interface with K means clusters 46 References fl Bederson B B Grosjean J and Meyer J Toolkit Design for Interactive Structured Graphics IEEE Transactions on Software Engineering 30 8 pp 535 546 2004 Benjamini Y and Hochberg Y Controlling the False Discovery Rate A Practical and Pow
79. um determined by the values of the Min and Maz parameters respectively Additionally if Fixed with parameters below option is selected the desired tick mark interval can also be specified through the Tick interval parameter If this option is set to Uniform all time points are placed at uniformly spaced intervals on the x axis on both the main interface and the profile details windows If this option is set to Based on real time time points are placed on the x axis proportionally spaced according to the real time points given in the column headers see Figure 23 The time points needs to be in the same units If STEM was unable to parse the time points then only the Uniform option is active 26 AILSTEM Profiles 1 Clusters ordered based on number of genes and profiles ordered by significance default De lalla SPIO WA TAHA UAN AANA MAR AMWAY All STEM Profiles 1 Clusters ordered based on number of genes and profiles ordered by significance default tata BSF 555854 RAR ARGAR i 7 ARS SASS Al AG ORS MAAR A a OMNA NN N oa fj AN FY ee l A RIP Profiles ordered based onthe actual size based p value of gene enrichment of GO 0007049 cell cycle genes aa ISS ASME Bae Bd be bed bad he be 1 A ba AA BA bd b Bd al BN EM AUA AA AMN Ei CN A EER Figure 22 Top left Main interface displaying all individual gene expression profiles with the y axis scale set to Gene specific specifi
80. ustering method Using K means in STEM is similar and the differences are discussed in Section 7 Most but not all of the information contained in this manual can also be obtained by clicking on the help icons throughout the software 1 3 Citing STEM To cite the STEM software please reference the paper Ernst J and Bar Joseph Z STEM a tool for the analysis of short time series gene expression data BMC Bioinformatics 7 191 2006 To specifically cite the STEM clustering method please reference the paper Ernst J Nau G J and Bar Joseph Z Clustering Short Time Series Gene Expression Data Bioinformatics 21 Suppl 1 pp 1159 1168 2005 2 Preliminaries To use STEM a version of Java 1 4 or later must be installed If Java 1 4 or later is not currently installed then it can be downloaded from http www java com To install STEM simply save the file stem zip locally and then unzip it This will create a directory called stem e To execute STEM in Windows with its default initialization options simply double click on the file stem cmd in the stem directory e To execute STEM from a command line change to the stem directory type and then type java mx1024M ms512M jar stem jar If Java gives an error message indicating that there is not enough memory on the computer available to start STEM then remove the msd12M option For slightly better time performance at the cost of more memory usage replace
81. will automatically be filtered if its expression value at the first time point is missing A user can also filter genes by criteria not implemented in STEM in which case a Pre filtered Gene File should be specified Below is a more detailed description of the parameters on the filtering panel e Maximum Number of Missing Values A gene will be filtered if the number of missing values exceeds this parameter e Minimum Correlation between Repeats This parameter controls filtering of genes which do not display a consistent temporal profile across repeat experiments and only applies if there is repeat data selected to be from Different time periods If there is a single repeat file a gene will be filtered if its correlation between the original data set and the repeat set is below this parameter If multiple repeats are available then the gene will be filtered if the median of all its pairwise correlations between experiments is below this parameter e Minimum Absolute Expression Change After transformation Log normalize data Normalize data or No Normalization add 0 if the absolute value of the gene s largest change is below this threshold then the gene will be filtered How change is defined depends on whether the Change should be based on parameter is set to Maximum Minimum or Difference from 0 see below e Change should be based on The Change should be based on parameter defines how cha
82. y since under some naming conventions the portion after the underscore is a symbol for the database that is not specific to the gene The DB_Object_Synonym column may have multiple symbols delimited by either a semicolon comma or a pipe symbol and all will be annotated as belonging to the GO category in Column 5 Note that the exact content of the DB_Object_ID DB_Object_Symbol DB_Object_Name and DB_Object_Synonym varies between annotation source consult the README files available at http www geneontology org GO current annotations shtm1 to find out more information about the content of these fields for a specific annotation source 2 The alternative format for an annotation file is two columns delimited by a tab as illustrated in Figure The first column contains gene symbols or spot IDs and the second column contains category IDs The entries in each column are delimited by a semicolon comma or a pipe symbol If the same gene symbol or spot ID appears on multiple rows then the union of all its annotations is used Matches between gene symbols in the data file and the annotation file is not case sensitive Gene annotation files can either be in an ASCII text format or a GNU zip file of an ASCII text file Below the Gene Annotation Source field is the Cross Reference Source field which controls the entry in the Cross Reference File field Cross references are usefu

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