flow cytometry data
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David ▴ 860
@david-3335
Last seen 6.0 years ago
Hi, I've recently got some data from the lab coming from flow cytometry. I have the log10 values corresponding to the geometrical mean (not the flow cytometry files). Basically i would like to start from that matrix and compute the fold changes. I'm not sure which test is most suitable as not sure which sitribution the data follows , gaussian ??? could anybody suggest how to move on from the log10 data matrix ? Any paper or tutorial . I have already looked at the flow packages within R but most of them deal with gating and scaling the raw data, but not how to compute fold changes thanks for any help, david
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@nolwenn-le-meur-3238
Last seen 9.6 years ago
Hi David, I am not such I see what are the data you are manipulating. What is the experimental design and biological question(s)? What represent the fold change you want to compute? What are the rows and columns in your log10 data matrix? For data analysis of cell-based assay, you might also want to have a look at the cellHTS2 package. Best, Nolwenn David martin wrote: > Hi, > I've recently got some data from the lab coming from flow cytometry. > I have the log10 values corresponding to the geometrical mean (not the > flow cytometry files). > > Basically i would like to start from that matrix and compute the fold > changes. I'm not sure which test is most suitable as not sure which > sitribution the data follows , gaussian ??? could anybody suggest how > to move on from the log10 data matrix ? Any paper or tutorial . > I have already looked at the flow packages within R but most of them > deal with gating and scaling the raw data, but not how to compute fold > changes > > thanks for any help, > david > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor -- Nolwenn Le Meur, PhD IRSET - Institut de Recherche en Sante-Environnement-Travail. INSERM/IRISA - Equipes INTEREST/Symbiose Universite de Rennes I Campus de Beaulieu 35042 Rennes cedex - France Phone: +33 2 99 84 71 17 Fax: +33 2 99 84 71 71 E-mail: nlemeur at irisa.fr Website: http://www.irisa.fr/symbiose/nolwenn_le_meur
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I have tested different cell surface markers on a sub population of monocytes. The matrix below shows a small snapshot of the different cell surface markers tested (cdA,cdB,cdC..) in different monocytes of patients that are either normal patients or treated patients. The values are the geomtrical mean obtained from the flow. They are log10 values. The question here is to identify markers differentually expressed in the monocytes subpopulation between normal patients and control patients. marker normal normal treated treated cdA -5.27 1.48 -1.28 -1.01 cdB -5.31 -1.89 9.31 1.01 cdC 4.12 8.1 8.16 3.6 cdE 30.44 11.59 3.39 14.64 CD11c 5.36 -1.48 -5.7 -4.44 Do i hve to normalize the data first ? I though this was already done by the instrument ? i might be wrong. Any idea ? Nolwenn Le Meur wrote: > Hi David, > > I am not such I see what are the data you are manipulating. What is the > experimental design and biological question(s)? What represent the fold > change you want to compute? What are the rows and columns in your log10 > data matrix? > > For data analysis of cell-based assay, you might also want to have a > look at the cellHTS2 package. > > Best, > Nolwenn > > David martin wrote: >> Hi, >> I've recently got some data from the lab coming from flow cytometry. >> I have the log10 values corresponding to the geometrical mean (not the >> flow cytometry files). >> >> Basically i would like to start from that matrix and compute the fold >> changes. I'm not sure which test is most suitable as not sure which >> sitribution the data follows , gaussian ??? could anybody suggest how >> to move on from the log10 data matrix ? Any paper or tutorial . >> I have already looked at the flow packages within R but most of them >> deal with gating and scaling the raw data, but not how to compute fold >> changes >> >> thanks for any help, >> david >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at stat.math.ethz.ch >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor > >
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David martin wrote: > > I have tested different cell surface markers on a sub population of > monocytes. The matrix below shows a small snapshot of the different > cell surface markers tested (cdA,cdB,cdC..) in different monocytes of > patients that are either normal patients or treated patients. > The values are the geomtrical mean obtained from the flow. They are > log10 values. > The question here is to identify markers differentually expressed in > the monocytes subpopulation between normal patients and control patients. > > marker normal normal treated treated > cdA -5.27 1.48 -1.28 -1.01 > cdB -5.31 -1.89 9.31 1.01 > cdC 4.12 8.1 8.16 3.6 > cdE 30.44 11.59 3.39 14.64 > CD11c 5.36 -1.48 -5.7 -4.44 > > > Do i hve to normalize the data first ? I though this was already done > by the instrument ? i might be wrong. Any idea ? I do not think you should normalize your data at that point. If any normalization would be required I think that it should be done on the raw data to correct for some bias identify by quality assessment analysis. Here you should have a look at the distribution of your data to choose between a parametric or non-parametric test (many you can find in R or BioC). Nolwenn > > > > Nolwenn Le Meur wrote: >> Hi David, >> >> I am not such I see what are the data you are manipulating. What is >> the experimental design and biological question(s)? What represent >> the fold change you want to compute? What are the rows and columns in >> your log10 data matrix? >> >> For data analysis of cell-based assay, you might also want to have a >> look at the cellHTS2 package. >> >> Best, >> Nolwenn >> >> David martin wrote: >>> Hi, >>> I've recently got some data from the lab coming from flow cytometry. >>> I have the log10 values corresponding to the geometrical mean (not >>> the flow cytometry files). >>> >>> Basically i would like to start from that matrix and compute the >>> fold changes. I'm not sure which test is most suitable as not sure >>> which sitribution the data follows , gaussian ??? could anybody >>> suggest how to move on from the log10 data matrix ? Any paper or >>> tutorial . >>> I have already looked at the flow packages within R but most of them >>> deal with gating and scaling the raw data, but not how to compute >>> fold changes >>> >>> thanks for any help, >>> david >>> >>> _______________________________________________ >>> Bioconductor mailing list >>> Bioconductor at stat.math.ethz.ch >>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>> Search the archives: >>> http://news.gmane.org/gmane.science.biology.informatics.conductor >> >> > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor -- Nolwenn Le Meur, PhD IRSET - Institut de Recherche en Sante-Environnement-Travail. INSERM/IRISA - Equipes INTEREST/Symbiose Universite de Rennes I Campus de Beaulieu 35042 Rennes cedex - France Phone: +33 2 99 84 71 17 Fax: +33 2 99 84 71 71 E-mail: nlemeur at irisa.fr Website: http://www.irisa.fr/symbiose/nolwenn_le_meur
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Sorry to ask but what are the tests ?? Nolwenn Le Meur wrote: > David martin wrote: >> >> I have tested different cell surface markers on a sub population of >> monocytes. The matrix below shows a small snapshot of the different >> cell surface markers tested (cdA,cdB,cdC..) in different monocytes of >> patients that are either normal patients or treated patients. >> The values are the geomtrical mean obtained from the flow. They are >> log10 values. >> The question here is to identify markers differentually expressed in >> the monocytes subpopulation between normal patients and control patients. >> >> marker normal normal treated treated >> cdA -5.27 1.48 -1.28 -1.01 >> cdB -5.31 -1.89 9.31 1.01 >> cdC 4.12 8.1 8.16 3.6 >> cdE 30.44 11.59 3.39 14.64 >> CD11c 5.36 -1.48 -5.7 -4.44 >> >> >> Do i hve to normalize the data first ? I though this was already done >> by the instrument ? i might be wrong. Any idea ? > I do not think you should normalize your data at that point. > If any normalization would be required I think that it should be done on > the raw data to correct for some bias identify by quality assessment > analysis. > > Here you should have a look at the distribution of your data to choose > between a parametric or non-parametric test (many you can find in R or > BioC). > > Nolwenn > >> >> >> >> Nolwenn Le Meur wrote: >>> Hi David, >>> >>> I am not such I see what are the data you are manipulating. What is >>> the experimental design and biological question(s)? What represent >>> the fold change you want to compute? What are the rows and columns in >>> your log10 data matrix? >>> >>> For data analysis of cell-based assay, you might also want to have a >>> look at the cellHTS2 package. >>> >>> Best, >>> Nolwenn >>> >>> David martin wrote: >>>> Hi, >>>> I've recently got some data from the lab coming from flow cytometry. >>>> I have the log10 values corresponding to the geometrical mean (not >>>> the flow cytometry files). >>>> >>>> Basically i would like to start from that matrix and compute the >>>> fold changes. I'm not sure which test is most suitable as not sure >>>> which sitribution the data follows , gaussian ??? could anybody >>>> suggest how to move on from the log10 data matrix ? Any paper or >>>> tutorial . >>>> I have already looked at the flow packages within R but most of them >>>> deal with gating and scaling the raw data, but not how to compute >>>> fold changes >>>> >>>> thanks for any help, >>>> david >>>> >>>> _______________________________________________ >>>> Bioconductor mailing list >>>> Bioconductor at stat.math.ethz.ch >>>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>>> Search the archives: >>>> http://news.gmane.org/gmane.science.biology.informatics.conductor >>> >>> >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at stat.math.ethz.ch >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor > >
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The usual choices for non-parametric location tests are the Mann?Whitney U test for independent samples, and the binomial test or the Wilcoxon signed-rank test for paired samples. The test depends on your sample see http://www.graphpad.com/www/Book/Choose.htm Have a look at the multtest package on Bioconductor and the mt.teststat function. It might help you. Nolwenn David martin wrote: > Sorry to ask but what are the tests ?? > > > Nolwenn Le Meur wrote: >> David martin wrote: >>> >>> I have tested different cell surface markers on a sub population of >>> monocytes. The matrix below shows a small snapshot of the different >>> cell surface markers tested (cdA,cdB,cdC..) in different monocytes >>> of patients that are either normal patients or treated patients. >>> The values are the geomtrical mean obtained from the flow. They are >>> log10 values. >>> The question here is to identify markers differentually expressed in >>> the monocytes subpopulation between normal patients and control >>> patients. >>> >>> marker normal normal treated treated >>> cdA -5.27 1.48 -1.28 -1.01 >>> cdB -5.31 -1.89 9.31 1.01 >>> cdC 4.12 8.1 8.16 3.6 >>> cdE 30.44 11.59 3.39 14.64 >>> CD11c 5.36 -1.48 -5.7 -4.44 >>> >>> >>> Do i hve to normalize the data first ? I though this was already >>> done by the instrument ? i might be wrong. Any idea ? >> I do not think you should normalize your data at that point. >> If any normalization would be required I think that it should be done >> on the raw data to correct for some bias identify by quality >> assessment analysis. >> >> Here you should have a look at the distribution of your data to >> choose between a parametric or non-parametric test (many you can find >> in R or BioC). >> >> Nolwenn >> >>> >>> >>> >>> Nolwenn Le Meur wrote: >>>> Hi David, >>>> >>>> I am not such I see what are the data you are manipulating. What is >>>> the experimental design and biological question(s)? What represent >>>> the fold change you want to compute? What are the rows and columns >>>> in your log10 data matrix? >>>> >>>> For data analysis of cell-based assay, you might also want to have >>>> a look at the cellHTS2 package. >>>> >>>> Best, >>>> Nolwenn >>>> >>>> David martin wrote: >>>>> Hi, >>>>> I've recently got some data from the lab coming from flow cytometry. >>>>> I have the log10 values corresponding to the geometrical mean (not >>>>> the flow cytometry files). >>>>> >>>>> Basically i would like to start from that matrix and compute the >>>>> fold changes. I'm not sure which test is most suitable as not sure >>>>> which sitribution the data follows , gaussian ??? could anybody >>>>> suggest how to move on from the log10 data matrix ? Any paper or >>>>> tutorial . >>>>> I have already looked at the flow packages within R but most of >>>>> them deal with gating and scaling the raw data, but not how to >>>>> compute fold changes >>>>> >>>>> thanks for any help, >>>>> david >>>>> >>>>> _______________________________________________ >>>>> Bioconductor mailing list >>>>> Bioconductor at stat.math.ethz.ch >>>>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>>>> Search the archives: >>>>> http://news.gmane.org/gmane.science.biology.informatics.conductor >>>> >>>> >>> >>> _______________________________________________ >>> Bioconductor mailing list >>> Bioconductor at stat.math.ethz.ch >>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>> Search the archives: >>> http://news.gmane.org/gmane.science.biology.informatics.conductor >> >> > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor -- Nolwenn Le Meur, PhD IRSET - Institut de Recherche en Sante-Environnement-Travail. INSERM/IRISA - Equipes INTEREST/Symbiose Universite de Rennes I Campus de Beaulieu 35042 Rennes cedex - France Phone: +33 2 99 84 71 17 Fax: +33 2 99 84 71 71 E-mail: nlemeur at irisa.fr Website: http://www.irisa.fr/symbiose/nolwenn_le_meur
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