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The document describes using the R statistical software to analyze flow cytometry data. It outlines the standard workflow which includes reading data files, performing transformations and compensation, gating the sperm population, normalizing the data, identifying subpopulations, and obtaining statistics. A practical example analyzes a semen sample stained for apoptosis, membrane integrity, and mitochondria that was evaluated at two time points. The results identify changes in the subpopulation percentages over time.

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The use of R statistical software to analyze flow cytometry data M. Ramón 1 , A. Maroto-Morales 1 , O. García-Álvarez 2 , P. Jimenez-Rabadán 2 , MD. Pérez-Guzmán 2 , F. Martínez-Pastor 3 , AJ. Soler 1 , JJ. Garde 1 1 IREC, (CSIC-UCLM-JCCM), Albacete; 2 CERSYRA, Valdepeñas; 3 ITRA-ULE-INDEGSAL, León 10º Congreso de la Asociación Española de Reproducción Animal Cáceres, 2-5 Junio 2010
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 R Statistical Software Integrated suite of software facilities for data manipulation, calculation and graphical display. WinMDI Version 2.9 Windows Multiple Document Interface for Flow Cytometry. The Scripps Research Institute (TSRI) WEASEL Version 2.7.4 Walter & Eliza Analysis Software: Eclectic & Lucid. The Walter and Eliza Hall Institute (WEHI)
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 Main Goal: To provide widespread access to a broad range of powerful statistical and graphical methods for the analysis of genomic data. Bioconductor provides a unified framework to develop methods to analyze and interpret Flow Cytometry data. Most common Packages α FlowCore α FlowUtils α FlowViz α FlowQ α FlowStats α FlowClust Bioconductor Open Source Software for Bioinformatics
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 1. READ DATA FILES > flowData <- read.flowSet( path =“.”, alter.names=TRUE, phenoData= “annotation.txt&quot;) > wf <- workFlow(flowData, name=&quot;Workflow #1&quot;)
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 1. READ DATA FILES > flowData <- read.flowSet( path =“.”, alter.names=TRUE, phenoData= “annotation.txt&quot;) > wf <- workFlow(flowData, name=&quot;Workflow #1&quot;) Organize standard flow cytometry data analysis in a workflow ,[object Object],[object Object],[object Object],> wf A flow cytometry workflow called 'Workflow #1' The following data views are provided: Basic view 'base view' on a flowSet not associated to a particular action item sampleId time stain file.001 Y.PI.MT.0 0H FL1.H/FL3.H/SSC.W file.002 Y.PI.MT.3 3H FL1.H/FL3.H/SSC.W …
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2. STANDARD FLOW OPERATIONS Scatter plot matrix
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2. STANDARD FLOW OPERATIONS Scatter plot matrix Some transformation is needed for better visualization of data
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2a. DATA TRANSFORMATION > tf <- transformList(colnames(flowData), asinh, transformationId=&quot;asinh&quot;) > add(wf,tf) > flowDataT <- transform(flowData, tf)
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 A new transformated flow data set 2a. DATA TRANSFORMATION > tf <- transformList(colnames(flowData), asinh, transformationId=&quot;asinh&quot;) > add(wf,tf) > flowDataT <- transform(flowData, tf) Assign new elements to an existing workflow ,[object Object],[object Object],[object Object],[object Object],[object Object]
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2a. DATA TRANSFORMATION Scatter plot matrix
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2b. IDENTIFICATION OF SPERM POPULATION FSC vs. SSC scatter plot > xyplot(`SSC.H` ~ `FSC.H` | sampleId, data=wf [[&quot;asinh&quot;]])
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2b. IDENTIFICATION OF SPERM POPULATION FSC vs. SSC scatter plot > xyplot(`SSC.H` ~ `FSC.H` | sampleId, data=wf [[&quot;asinh&quot;]]) Debris
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2b. IDENTIFICATION OF SPERM POPULATION FSC vs. SSC scatter plot > sp.gate <- polygonGate(.gate=r01) > add(wf, sp.gate, parent='asinh')
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2b. IDENTIFICATION OF SPERM POPULATION FSC vs. SSC scatter plot WinMDI WEASEL
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 3. MEMBRANE INTEGRITY STUDY YO-PRO®-1 (FL1.H) vs. PI (FL3.H) scatter plot > xyplot(`FL3.H` ~ `FL1.H` | sampleId, data=wf[[&quot;asinh&quot;]]) RAW DATA
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 3. MEMBRANE INTEGRITY STUDY YO-PRO®-1 (FL1.H) vs. PI (FL3.H) scatter plot > xyplot(`FL3.H` ~ `FL1.H` | sampleId, data=wf[[&quot;asinh&quot;]]) Debris must be removed !!! RAW DATA
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 3. MEMBRANE INTEGRITY STUDY YO-PRO®-1 (FL1.H) vs. PI (FL3.H) scatter plot > xyplot(`FL3.H` ~ `FL1.H` | sampleId, data=wf[[&quot;asinh&quot;]]) RAW DATA SUBSET SPERM POPULATION
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 3. MEMBRANE INTEGRITY STUDY YO-PRO®-1 (FL1.H) vs. PI (FL3.H) scatter plot > xyplot(`FL3.H` ~ `FL1.H` | sampleId, data=wf[[&quot;asinh&quot;]]) Is a compensation of data needed? Must be applied before data transformation !! SUBSET SPERM POPULATION
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],FL1.H FL2.H FL3.H FL4.H FL5.H [1,] 1 0.240 0.032 0.001 0 [2,] 0.008 1 0.140 0.003 0 [3,] 0.170 0.170 1 0.210 0 [4,] 0.001 0.001 0.003 1 0 [5,] 0 0 0 0 1
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2c. DATA COMPENSATION COMPENSATION MATRIX
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2c. DATA COMPENSATION COMPENSATION MATRIX WEASEL
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 3. MEMBRANE INTEGRITY STUDY IDENTIFICATION OF DIFFERENT SUBPOPULATIONS Definition of Regions/Quadrants ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 3. MEMBRANE INTEGRITY STUDY IDENTIFICATION OF DIFFERENT SUBPOPULATIONS RECTANGLE REGION POLYGON REGIONS QUADRANT REGIONS
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 3. MEMBRANE INTEGRITY STUDY IDENTIFICATION OF DIFFERENT SUBPOPULATIONS QUADRANT REGIONS
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 3. MEMBRANE INTEGRITY STUDY IDENTIFICATION OF DIFFERENT SUBPOPULATIONS Definition of Regions/Quadrants Regions are different for each semen sample Data normalization will allow the use of a single region or quadrant set
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2d. DATA NORMALIZATION > norm <- normalization(parameters=param, normalizationId=&quot;norm&quot;, + normFunction=function(x, parameters, ...) warpSet(x,parameters)) > add(wf, norm, parent=&quot;asinh&quot;) BEFORE NORMALIZATION
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2d. DATA NORMALIZATION > norm <- normalization(parameters=param, normalizationId=&quot;norm&quot;, + normFunction=function(x, parameters, ...) warpSet(x,parameters)) > add(wf, norm, parent=&quot;asinh&quot;) AFTER NORMALIZATION
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 3. MEMBRANE INTEGRITY STUDY IDENTIFICATION OF DIFFERENT SUBPOPULATIONS Summarize statistics FL1.H-FL3.H- FL1.H+FL3.H- FL1.H+FL3.H+ Y.PI.MT.0 47.77% 33.68% 18.37% Y.PI.MT.3 53.65% 30.28% 15.15%
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 7. iFLOW
The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 THANK YOU FOR YOUR ATTENTION

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mramon_AERA2010

  • 1. The use of R statistical software to analyze flow cytometry data M. Ramón 1 , A. Maroto-Morales 1 , O. García-Álvarez 2 , P. Jimenez-Rabadán 2 , MD. Pérez-Guzmán 2 , F. Martínez-Pastor 3 , AJ. Soler 1 , JJ. Garde 1 1 IREC, (CSIC-UCLM-JCCM), Albacete; 2 CERSYRA, Valdepeñas; 3 ITRA-ULE-INDEGSAL, León 10º Congreso de la Asociación Española de Reproducción Animal Cáceres, 2-5 Junio 2010
  • 2. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 R Statistical Software Integrated suite of software facilities for data manipulation, calculation and graphical display. WinMDI Version 2.9 Windows Multiple Document Interface for Flow Cytometry. The Scripps Research Institute (TSRI) WEASEL Version 2.7.4 Walter & Eliza Analysis Software: Eclectic & Lucid. The Walter and Eliza Hall Institute (WEHI)
  • 3. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 Main Goal: To provide widespread access to a broad range of powerful statistical and graphical methods for the analysis of genomic data. Bioconductor provides a unified framework to develop methods to analyze and interpret Flow Cytometry data. Most common Packages α FlowCore α FlowUtils α FlowViz α FlowQ α FlowStats α FlowClust Bioconductor Open Source Software for Bioinformatics
  • 4.
  • 5. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 1. READ DATA FILES > flowData <- read.flowSet( path =“.”, alter.names=TRUE, phenoData= “annotation.txt&quot;) > wf <- workFlow(flowData, name=&quot;Workflow #1&quot;)
  • 6.
  • 7.
  • 8. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2. STANDARD FLOW OPERATIONS Scatter plot matrix
  • 9. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2. STANDARD FLOW OPERATIONS Scatter plot matrix Some transformation is needed for better visualization of data
  • 10. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2a. DATA TRANSFORMATION > tf <- transformList(colnames(flowData), asinh, transformationId=&quot;asinh&quot;) > add(wf,tf) > flowDataT <- transform(flowData, tf)
  • 11.
  • 12. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2a. DATA TRANSFORMATION Scatter plot matrix
  • 13. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2b. IDENTIFICATION OF SPERM POPULATION FSC vs. SSC scatter plot > xyplot(`SSC.H` ~ `FSC.H` | sampleId, data=wf [[&quot;asinh&quot;]])
  • 14. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2b. IDENTIFICATION OF SPERM POPULATION FSC vs. SSC scatter plot > xyplot(`SSC.H` ~ `FSC.H` | sampleId, data=wf [[&quot;asinh&quot;]]) Debris
  • 15. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2b. IDENTIFICATION OF SPERM POPULATION FSC vs. SSC scatter plot > sp.gate <- polygonGate(.gate=r01) > add(wf, sp.gate, parent='asinh')
  • 16. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2b. IDENTIFICATION OF SPERM POPULATION FSC vs. SSC scatter plot WinMDI WEASEL
  • 17. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 3. MEMBRANE INTEGRITY STUDY YO-PRO®-1 (FL1.H) vs. PI (FL3.H) scatter plot > xyplot(`FL3.H` ~ `FL1.H` | sampleId, data=wf[[&quot;asinh&quot;]]) RAW DATA
  • 18. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 3. MEMBRANE INTEGRITY STUDY YO-PRO®-1 (FL1.H) vs. PI (FL3.H) scatter plot > xyplot(`FL3.H` ~ `FL1.H` | sampleId, data=wf[[&quot;asinh&quot;]]) Debris must be removed !!! RAW DATA
  • 19. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 3. MEMBRANE INTEGRITY STUDY YO-PRO®-1 (FL1.H) vs. PI (FL3.H) scatter plot > xyplot(`FL3.H` ~ `FL1.H` | sampleId, data=wf[[&quot;asinh&quot;]]) RAW DATA SUBSET SPERM POPULATION
  • 20. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 3. MEMBRANE INTEGRITY STUDY YO-PRO®-1 (FL1.H) vs. PI (FL3.H) scatter plot > xyplot(`FL3.H` ~ `FL1.H` | sampleId, data=wf[[&quot;asinh&quot;]]) Is a compensation of data needed? Must be applied before data transformation !! SUBSET SPERM POPULATION
  • 21.
  • 22.
  • 23. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2c. DATA COMPENSATION COMPENSATION MATRIX
  • 24. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2c. DATA COMPENSATION COMPENSATION MATRIX WEASEL
  • 25.
  • 26. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 3. MEMBRANE INTEGRITY STUDY IDENTIFICATION OF DIFFERENT SUBPOPULATIONS RECTANGLE REGION POLYGON REGIONS QUADRANT REGIONS
  • 27. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 3. MEMBRANE INTEGRITY STUDY IDENTIFICATION OF DIFFERENT SUBPOPULATIONS QUADRANT REGIONS
  • 28. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 3. MEMBRANE INTEGRITY STUDY IDENTIFICATION OF DIFFERENT SUBPOPULATIONS Definition of Regions/Quadrants Regions are different for each semen sample Data normalization will allow the use of a single region or quadrant set
  • 29. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2d. DATA NORMALIZATION > norm <- normalization(parameters=param, normalizationId=&quot;norm&quot;, + normFunction=function(x, parameters, ...) warpSet(x,parameters)) > add(wf, norm, parent=&quot;asinh&quot;) BEFORE NORMALIZATION
  • 30. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 2d. DATA NORMALIZATION > norm <- normalization(parameters=param, normalizationId=&quot;norm&quot;, + normFunction=function(x, parameters, ...) warpSet(x,parameters)) > add(wf, norm, parent=&quot;asinh&quot;) AFTER NORMALIZATION
  • 31. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 3. MEMBRANE INTEGRITY STUDY IDENTIFICATION OF DIFFERENT SUBPOPULATIONS Summarize statistics FL1.H-FL3.H- FL1.H+FL3.H- FL1.H+FL3.H+ Y.PI.MT.0 47.77% 33.68% 18.37% Y.PI.MT.3 53.65% 30.28% 15.15%
  • 32.
  • 33.
  • 34. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 7. iFLOW
  • 35. The use of R statistical software to analyze flow cytometry data 10º Congreso de la Asociación Española de Reproducción Animal (AERA) Cáceres, 2-5 Junio 2010 THANK YOU FOR YOUR ATTENTION