Spatial intensity distribution analysis Matlab user guide
Contents
1. gt gt gt gt Workspace pex gt gt fa m 55 Sp HS Select dat gt gt GuI_sprpal 1 Details 2 Load an image a After the initial launch an explorer window will open and offer you to load some image file The images can be single image time series or Z stack If the loaded file contains more than one image a scroll bar will appear to permit navigation through images The chosen folder will be saved for subsequent image loading To load another image just click in the load image textbox on top of the GUI Doo yyy Look in J GUI SpIDA v1 2 amp ek Ee Name Date Type a Recent Places Desktop E Testlmage_EGFR GFP_20nM tif 1 30 2009 1 03 PM TIF File S Testimage mGFP f tif 1 30 2009 11 18 AM TIF File File name Testlmage mGFP4 tif Files of type All Image Files GUI SpIDA D Data SpIDA FunctionsiGUI SpIDA v1 21Testlmage mGFP tif Load image 1 textbox 0 9 0 8 0 7 0 6 0 5 0 4 0 3 0 2 0 1 0 0 Populations Pop 1 Region to analyze BE r ee E Results SpIDA xp yp Areas Area Amplitude Density QB Chose Region Square Bin 50 5000 Draw Region Res 247 PMT Noise Normalize 7 Save with Chose Region E Save with Save all2. Save Histo and region 3 Setthe correct parameters for the image file a The GUI will attempt to obtain the information from the file itself If it cannot a dialog box will appear and the correct image information can be manually set The pixel size and the beam waist radius in micron are needed The pixel size depends on the microscope settings objective zoom size of image and the beam size which is defined as the point spread function PSF mostly depend of the laser used and the PSF for each laser line can be characterized using small fluorescent micropheres Enter the pixel size here Enter the beam size here 0 2 4 Understand the histogram parameters a The White Noise WN corresponds to the intensity value when the laser is off Usually it can be estimated by taking the mean intensity of a region in an image where no cells fluorophores are present b The histogram intensity bin can be changed by varying the number in the box Bin It will change the number of points in the histogram It can be modified to change the analyzing time but should not affect the results on a wide value range c The resolution Res is defined here as the number of pixels included in the beam waist radius i e Wyy pixel size d Anintensity threshold can be included in the fit of the histogram and can be modified by changing the value in the boxes Th The analysis will consider only the pixels between Thmin and Thmax 5 Ch
3. a Gaussian noise function at all intensities It is important to note that the slope can depend on many parameters dwell time PMT voltage scan speed temperature etc and that for each set of parameters the calibration should be made Similar calibration can be done for a CCD camera by generating movies of constant stable light source and generating a graph of the variance of each pixel as a function of the mean intensity b 4 m PMT 600V slope 36 5 iu S 4 PMT 800V oh aay f E 4 linear fit eS s m 72 A AA 9 8 lope 7 91 o a slope 7 9 iu e ET ix at 10 2x10 3x10 4 10 5x10 mean pixel intensity 1u
4. by changing the Pop Monomer Dimer means that there are a mixture of monomers and dimers in the image The monomeric quantal brightness can also be fixed in the fit The monomeric quantal brightness can be estimated using samples expressing monomeric fluorescent proteins e g mGFP or by measuring the quantal brightness of fluorescent secondary antibodies depending on the systems and probes used A dimer will then be twice as bright as a monomer If the monomeric quantal brightness is set to O the monomeric quantal brightness will also be fit The results of the fits are shown in the box Results SpIDA i The Area is the area of the chosen region in beam areas pi Wy The amplitude of the fit is the height of the histogram in pixels iii The density of the each of the population is also given The density has units of particles per effective illumination volume This effective volume can be a surface if the region chosen is on the cell membrane Or a volume if the ROI is completely included in a cell e g cytoplasm or nucleus then the volume can be approximated as the effective volume of a three dimensional Gaussian pi W W iV The quantal brightness is the average brightness of a fluorescent entity in the effective volume and has units of intensity b Todoan analysis with noise correction The Slope Variance textbox will appear by clicking on the PMT Noise check box After ade
5. 73173847 12064002 i eo 0 00000000000000Q0Q0e 000 0 QOOOOODOQOQOOQOQO0g s Mean Standard Min intensity in Max intensity in intensity deviation of the ROI ROI intensity Set white noise value Detector calibration SpIDA studies the fluctuations of the signal in the image to give information on the number of particles and their quantal brightness for this reason it is important to consider only the fluctuations that originate from the signal and not the detector To calibrate the detector it is important to empirically determine the inherent noise over the entire output range of the PMT for our system Because SpIDA is based on the assumption that the measured intensity is linearly proportional to the photon counts it 1s important to confirm that the response of the PMT is linear over the range of intensity used in the experiment Standard Deviation iu S S 0 0 0 0 1 0 2 0 3 0 4 LASER power mW To do this one can look at the back reflection of the laser from a mirror or using an extremely dense fluorescent slide and measure as a function of time the intensity from a point scan measurement Using this technique a graph of the variance of the signal vs the mean intensity can be graphed An example the variance of the back reflection vs the mean intensity of each measurement is presented lower Using this the SpIDA histograms incorporating this detector noise for one or two populations can be obtained assuming
6. Spatial intensity distribution analysis Matlab user guide August 2011 Guide on how to use the SpIDA graphical user interface This little tutorial provides a step by step tutorial explaining how to get started using the GUI SpIDA This software is provided as is without any warranty whatsoever For any comments feedbacks or question do not hesitate to contact spidagui gmail com This GUI should work on most operating systems it was tested on Windows 32 and 64 bits MAC OS X and UNIX as long as you have a recent version of MaTLAB This GUI was created on MaTLAB Version 7 10 0 499 R2010a 64 bit win64 but should work on most of older versions Standalone compiled versions are also available for users that do not have MaTLAB licenses or have a license that does not include needed toolboxes The appropriate MCRInstaller exe first has to be installed before being able to use the GUI For now only the Windows 32bit and 64bits versions are available 1 Launch GUI SpIDA to start using the program It is important to set the Current Folder to the directory that contains the GUI files 6 MATLAB 7 100 82010 ees File Edit Debug Parallel Desktop Window Help LOS AAA J d rd E Current Folder D Data SpIDA Functions GULSpIDA v1 2 m B Shortcuts Howto Add 2 What s New Current Folder M aL Load Gui SpIDA 2 GD New to MATLAB Watch this Video see Demos or read Getting Started gt gt gt gt
7. ely to save on the number of clicks Qus ri ess Quantal brightness Quantal brightness Area of ROI Ampi Density pr BA iu Amp2 Density iia BA 2 BAS em SSS i CE Fle Im Format fees He 2168752 002 1 0669315456459656 00000000 0 0000000000000000 000 0 00000000000000006 000 9387 34 erbe 7297 e1002 0 DODGE ME ARES Resolution number pineisin v xy 0000000000000000 000 1722321495476544e 000 0 0000000000000000e4000 ARATRO 540061000 001 2 85381589649570025 amp 001 0 00000000 o 000 2000 Positions defining the ROI 1 000000Q000000000 000 4 000000000000000 2000 0 00000008Q0000000e 000 0 ooo Slope of detector noise variance 908000 000 D 000 0 00000000000000004 C creer recte tnn tan sad Hees COD 0 00000000 000 0 0000000000000000 000 0 0000000000000000e 000 0 0000 0 000000000000 1 if PIT Noise ison 900 0 0000000000000000e 000 0 0000000000000000e 0 0000 alues Min max 000 0 000000000000X O00 0 0000000000000000e 000 0 0000000000000000 000 0 000 000 0 0000000000000000e 000 0 OL OC 00 0 Oe 000 0 0000000000000000 000 Q 0D00000000000000e 09 OOO0O0O0000O00O000000e 000 0 0000000000000000 000 0 0000000000000000e 000 0 0000000000000000 000 3 em em 1 09609
8. ose a region of interest ROI to analyze a The button Chose Region will enable the selection of a region to analyze Clicking twice on the image after pressing on the button Chose Region will delimitate a rectangle region The two chosen pixel positions are shown to the left of the two buttons Chose Region and Draw Region b The button Draw Region refreshes the image with the new coordinates if changed and the intensity histogram with the histogram parameters A zoom of the chosen region with enhanced contrast is also presented in the lower part of the GUI c The check box Normalize in the on position will change the contrast and make only the pixels of the image in the threshold range visible This only affects the visualization of the image and does not change the analysis D Data SpIDA Functions GUI SpIDA 1 21 mGFP tif Frequency 500 1000 Intensity GO Region to analyze Histogram Results SpIDA Beam 997 9 WN yp Areas 190 Th 0 Area Amplitude Density QB 404 Chose Region Square 10 1500 Draw Region ES 217 PMT Noise 4 Normalize Save with Chose Region Save all 6 Run the analysis a After the selection of the region to be analyzed and by setting the histogram parameters Clicking on the GO button will run the SpIDA analysis on the selected subregion The number of populations in the SpIDA fit can be set to 2
9. quate detector calibration see Detector calibration section lower and setting the appropriate value for the slope of the variance as a function of the mean Slope Variance Again clicking on the button GO will run the SpIDA analysis and the results will appear in the box Results SpIDA For each set of imaging parameters this should be done for obtaining accurate results es EE aS D Data SpIDA Functions GUISpIDA_v1 2 TestImage_mGFP fif Frequency co ex 500 1000 Intensity GO Populations Pop 1 v Region to analyze Bean Histogram Results SpIDA m vi reas 997 9 WN 150 Th 0 Area Amplitude Density QB 788 404 Chose Region Square 10 1500 093 9 632 107 29 898 536 Draw Region ES 2 17 V PMT Noise 7 Normalize E Save with Chose Region Slope 9 Save with Go Variance Save all E Bx Save Histo and region 7 Savethe results To save the results of an analysis just press the button Save all and the GUI will save a dat file with the name of the image with all the fit values and set parameters If the button Save with Go is activated the results will be saved automatically in the chosen folder when the analysis is done whereas when the button Save with Choose Region is set to true the analysis will be launched and the results will be saved automatically Those two options exist ultimat
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