[BioC] Very Different group sizes in DE of two conditions

[Moriah [guest]]

Hi,

I would like to conduct DE analysis of miRNA and mRNA using DESeq and EdgeR  on two conditions (Breast cancer subtypes) the problem is that for one condition I have 122 samples and for the second only 22.  I would like to know if it is O.K to run DE on such different size groups ?

What I tried to do is to run 100 different permutations of 22 samples out of 122 and to try to run DE and search for differentially expressed miRNA in all 100 different permutations against the 22 from the second condition.

I got only one miRNA that is differentially expressed in DESeq in all permutaions but when I run 122 samples against 22 samples I got no such miRNA. There is a difference between EdgeR results as well.

Is my way of creating samller groups is applicable? Or is there any other way to deal with such different group sizes?

Thanks!

 -- output of sessionInfo(): 

R version 2.15.1 (2012-06-22)
Platform: x86_64-pc-linux-gnu (64-bit)

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=C                 LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
[1] edgeR_2.6.7    limma_3.12.1   DESeq_1.8.3    locfit_1.5-8   Biobase_2.14.0

loaded via a namespace (and not attached):
 [1] annotate_1.34.0      AnnotationDbi_1.18.1 BiocGenerics_0.2.0  
 [4] DBI_0.2-5            genefilter_1.38.0    geneplotter_1.34.0  
 [7] grid_2.15.1          IRanges_1.14.3       lattice_0.20-6      
[10] RColorBrewer_1.0-5   RSQLite_0.11.1       splines_2.15.1      
[13] stats4_2.15.1        survival_2.36-14     xtable_1.7-0  
>

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