[BioC] flow cytometry data
Nolwenn Le Meur
nlemeur at irisa.fr
Thu Dec 3 14:13:48 CET 2009
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
>>>>>
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>>>>
>>>>
>>>
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>>
>>
>
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--
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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