[BioC] (adj.p.value & log2FC) or (B.value & log2FC)

[Richard Friedman]

Dear Deb,

	I used adjusted.p.value (with fdr) <0.05 because it takes multiple
tests into account in computing the signficance.
If I have fewer than (say) 50 genes I make the fdr more lenient.
If more that 1K genes, I filter by the absolute value of log2FC as well.

with hopes that the above helps,
Rich
On Dec 2, 2013, at 1:15 PM, deb [guest] wrote:

> 
> Hi Sir,
> I have a simple question regarding cut-off parameter to be used for filtering out DEGs from the topT object obtained using LIMMA.
> Which statistics is preferred more and why?
> 1) filter of adj.p.value and log2FC.
> 2) filter of B.value and log2FC.
> I mean both give similar ranking of genes but usually I have  seen people using an adj.p.value cut-off of 0.01. What is the minimum cut-off value for B.value?(Is it 4?)
> It is a technical question so I do not have any output to be put in the next sessionInfo() field.
> Thank you for your input Sir.
> Regards.
> Deb.
> 
> 
> 
> -- output of sessionInfo(): 
> 
> topT<- topTable(fit3, coef=1, adjust="BH", sort.by="B",number=nrow(data))
> 
> 
> --
> Sent via the guest posting facility at bioconductor.org.
> 
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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)/
Columbia Department of Systems Biology
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://friedman.c2b2.columbia.edu/ 

In memoriam, Frederik Pohl