[BioC] necessity of moderated t statistic and false discoveries for small predefined gene list?
Y-h. Taguchi
tag at granular.com
Thu May 17 02:34:26 CEST 2012
Dear Rich & Moshe,
I am not sure if cotinuation of this discussion here is suitable for
this ml or not, but I will comment.
Although I do not know what Rich intends to mean by the term
"differential expression",
I am sure that
1) t-statistics
and
2) log (Fold change)
are not enough.
try
t.test(c(1,2,3),c(4,5,6))
and
t. test(c(10,20,30),c(40,50,60))
They provide you the same t-statistics and fold change. However, these
two can have different meanings biologically, if both c(1,2,3,4,5,6)
and c(10,20,30,40,50,60) have already been normalized to some control
signal.
yours, tag.
2012/5/17 Moshe Olshansky <olshansky at wehi.edu.au>:
> Hi Rich,
>
> Whether to use the moderated t-statistic or not does not depend on whether
> you are interested in the 10 particular genes or in all differentially
> expressed ones. This will affect your multiple testing adjustment.
> The simplest way for you to proceed is to use limma as usual, get the
> topTable but then take the UNADJUSTED p-values for your 10 genes of
> interest and use the p.adjust function to adjust for multiple testing if
> you wish. In any case you should also look at (log)Fold Changes.
>
> Best regards,
> Moshe.
>
>
>> Dear Bioconductor List.
>>
>> I am using Limma to analyze differential expression between 2
>> conditions on an Affy chip.
>> My experimental collaborator asks for the differential expression of
>> 10 predefined genes.
>>
>> A, Should I correct for false discoveries based upon all of the genes
>> on the chip?
>> B. If not, should I correct for false discoveries just for the
>> probeids for the 10 predefined
>> genes?
>> C. Should I use the moderated t-statistic or just use an unmoderated t-
>> test for those 10
>> genes.
>>
>> Thanks and best wishes,
>> Rich
>> ------------------------------------------------------------
>> Richard A. Friedman, PhD
>> Associate Research Scientist,
>> Biomedical Informatics Shared Resource
>> Herbert Irving Comprehensive Cancer Center (HICCC)
>> Lecturer,
>> Department of Biomedical Informatics (DBMI)
>> Educational Coordinator,
>> Center for Computational Biology and Bioinformatics (C2B2)/
>> National Center for Multiscale Analysis of Genomic Networks (MAGNet)
>> Room 824
>> Irving Cancer Research Center
>> Columbia University
>> 1130 St. Nicholas Ave
>> New York, NY 10032
>> (212)851-4765 (voice)
>> friedman at cancercenter.columbia.edu
>> http://cancercenter.columbia.edu/~friedman/
>>
>> "School is an evil plot to suppress my individuality"
>>
>> Rose Friedman, age15
>>
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>
>
> --
> Moshe Olshansky
> Division of Bioinformatics
> The Walter & Eliza Hall Institute of Medical Research
> 1G Royal Parade, Parkville, Vic 3052
> e-mail: olshansky at wehi.edu.au
> tel: (03) 9345 2849
>
>
> ______________________________________________________________________
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