[BioC] edgeR and tagwise dispersion: overcorrection for multiple tests?

[alessandro.guffanti at genomnia.com]

Dear colleagues good morning - I am back to an old issue because I am 
now much more
certain of what I see - and I begin to wonder wether this is due to 
biology rather than
to analytical tools or strategies ..

=> Here is my sessionInfo() to  begin with:

R version 2.15.0 (2012-03-30)
Platform: x86_64-pc-mingw32/x64 (64-bit)

locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252

attached base packages:
[1] stats     graphics  grDevices datasets  utils     methods base

other attached packages:
[1] edgeR_2.6.7       limma_3.12.1      R.utils_1.12.1 R.oo_1.9.8
[5] R.methodsS3_1.4.2

=> the experiment description: RNA from five samples and five controls, 
mice,
homogenesous stimulus, brain tissue, SAGE with SOLiD with a good mapping
in the UTR (checked also with genome-wide mapping). Tags have been selected
with the following parameters: only in UTR; unique mapping; only one 
mismatch;
begin with CATG, hence quite stringent. Hence tha samples are tagged {1 
to 5}R
for ths stimulus, {1 to 5} as the control

=> MDS plot and simple pairwise regression analysis of the tag counts 
between
R,C,R vs R and C vs C reveals a clear division of the R samples in two 
groups:
{1R, 3R} and {2R,4R,5R}. In addition, one C sample (3C) overlaps with 
two R samples
and is removed from comparisons

=> three DEG calculations were performed:
(A) all C vs all R;
(B) all C minus 3 C vs 1R + 3R;
(C) all C minus 3 C versus {2R,4R,5R}

=> tagwise dispersion; normalizatuion factor on the libraries 
calculated;  filtering by minimal CPM in samples leaves between 6000 and 
7000 genes for each comparison.

=> results which make me wonder about what is happening in the R 
(esperiment) samples:

Comparison A (ALL vs ALL): TWO genes with significant FDR (BH corrected 
PValue I understand)
Comparison B (ALL-3C vs 1R,3R): 2099 genes with significant FDR (!)
Comparison C (ALL-3C vs 2R,4R,5R): 20 genes with significant FDR

Now, excuse my ignorance, but this is a rather strong effect of the 
subsetting of one of the two comparison
datasets on the FDR, which I did not found in many other similar 
analyses. In fact, when I first mailed the list,
I was talking about 'overcorrection for multiple tests'.

Is there any reasonable explanation (apart from {1R,3R} and {2R,4R,5R} 
being totally different samples, which I exclude) for this ? maybe a 
strong dependency between the genes involved in the response to the 
stimulus in the
two R subgroups ?

I include below the three MDS plots - thanks for any answer and again 
excuse me, maybe there is a trivial
reason for this (such as number of samples..) but it is an unqiue 
situation between my many SAGE experiments
analyzed with edgeR..

Kind regards,

Alessandro

--







-- 

Alessandro Guffanti - Head, Bioinformatics, Genomnia srl
  Via Nerviano, 31 - 20020 Lainate, Milano, Italy
     Ph: +39-0293305.702 Fax: +39-0293305.777
             http://www.genomnia.com
"When you're curious, you find lots of interesting things to do."
(Walt Disney)



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