Dear colleagues: I am analyzing the result of some cancer samples miRNA NGS 
experiments with edgeR, with the following setup:

R version 2.15.3 (2013-03-01)
Platform: x86_64-w64-mingw32/x64 (64-bit)

locale:
[1] LC_COLLATE=Italian_Italy.1252  LC_CTYPE=Italian_Italy.1252   
[3] LC_MONETARY=Italian_Italy.1252 LC_NUMERIC=C                  
[5] LC_TIME=Italian_Italy.1252    

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

other attached packages:
[1] edgeR_3.0.8  limma_3.14.4

I am following a rather standard workflow - please note that we have 8 
samples and only 1 control

> targets <- read.delim("targets.txt", stringsAsFactors = FALSE)
> d <- readDGE(targets, header=FALSE)
> colnames(d) <- 
c("ARMS1","ARMS2","ARMS3","ARMS4","ERMS1","ERMS2","ERMS3","ERMS4","NMS")
> dim(d)
[1] 2038    9
>keep <- rowSums(cpm(d)> 5) >= 3
> dim(d)
[1] 685   9
> d$samples$lib.size <- colSums(d$counts)
> d<-calcNormFactors(d)
> d <- estimateCommonDisp(d, verbose=TRUE)
Disp = 0.71417 , BCV = 0.8451
> d <- estimateTagwiseDisp(d, trend="none",verbose=TRUE)
Using interpolation to estimate tagwise dispersion.
> de.com <- exactTest(d)
> sum(de.com$table$PValue < 0.05)
[1] 97
> topValues <- topTags(de.com,n=97)
> summary(decideTestsDGE(de.com,p.value=0.05))
[,1]
-1   44
0   641
1     0

What we noticed is that there is a strong asimmetry in the corrected P 
values, in that only the downregulated miRNAs have a significant corrected P 
value - the upregulated miRNAs are less when examing the uncorreetd counts, 
basically we have alf of the CPM

Questions:

=> is the unbalanced experimental design affecting the results ? this 
unbalance is coherent with the literature, in cancers the majority of miRNAs 
are downregulated

=> if yes, can I correct it or we should just take the results as they are 
and validate extensively if we want to explore also the upregulated miRNAs ?

Thanks a lot in advance for any help,

Alessandro & colleagues
-----------------------------------------------------
Alessandro Guffanti - Head, Bioinformatics
Genomnia srl
Via Nerviano, 31/B – 20020 Lainate (MI)
Tel. +39-0293305.702 / Fax +39-0293305.777
www.genomnia.com [http://www.genomnia.com/]
alessandro.guffanti@genomnia.com [mailto:alessandro.guffanti@genomnia.com]

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