[BioC] help: limma and changing gene results!

[Koen Marien]

Dear


Is this also the reason why there is a difference in the (differentially
expressed) gene lists of a-(b+c+d) and venny(a-b,a-c,a-d)?

a-(b+c+d): 				putting the b, c and d values in one
group (b+c+d) and using limma
venny(a-b,a-c,a-d): 		using limma on the separate groups and
create a list by looking at the intersection of de venn diagram of the three

					'sublists' a-b, a-c, a-d


Thanks a lot


Koen Marien
student bioscience engineering: cell and gene biotechnology
University of Ghent, Belgium


-----Original Message-----
From: bioconductor-bounces at stat.math.ethz.ch
[mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of James W.
MacDonald
Sent: donderdag 29 april 2010 18:46
To: Joseph Skaf
Cc: bioconductor at stat.math.ethz.ch
Subject: Re: [BioC] help: limma and changing gene results!

Hi Joseph,

Joseph Skaf wrote:
> To whom it may concern,
> 
> I've been having some problems with consistency in my limma results for
> genes that are found to have significant differential transcript
abundance.
> 
> In a given example, I may have 4 different groups (a, b, c, and d) in an
> array set of 12.
> 
> From here, I make a contrast matrix that has contrasts for a-b, a-c, and
> a-d.  Eventually, I output an eBaye's corrected contrast fit and I use
> decideTests from there to find out what genes are differentially
expressed.
> My misunderstanding is that when I take away an entire group (such as
> removing all d's) and redo all steps in the limma analysis, I find that I
> end up with a different set of genes after using decideTests.  I am
confused
> here, because I would not think that removing group 'd' from the analysis
> would have an effect on contrasts a-b and a-c.
> 
> If anyone could even hint to me a reason as to why this is happening, it
> would be greatly appreciated.

It's because of how the denominator for your contrast is computed. The 
denominator is computed using the intra-group variance for all the 
groups in your study, not just the two groups being compared in the 
contrast.

So if you remove one of the groups, you lose both degrees of freedom as 
well as the contribution from the intra-group variance of that group. 
Losing the degrees of freedom will reduce your power to detect 
differences. Losing the contribution of the intra-group variance will 
depend on how variable the group d data are compared to groups a-c.

Best,

Jim



> 
> Thanks and regards,
> Joseph Skaf
> 
> 
> 

-- 
James W. MacDonald, M.S.
Biostatistician
Douglas Lab
University of Michigan
Department of Human Genetics
5912 Buhl
1241 E. Catherine St.
Ann Arbor MI 48109-5618
734-615-7826
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