[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


2) log (Fold change)

are not enough.




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

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
> ______________________________________________________________________
> The information in this email is confidential and inte...{{dropped:15}}

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