[BioC] fold change, low count reads filter

[Vittoria Roncalli [guest]]

Hi, 
I am new user of edgeR for gene expression analysis. I am testing three different condition, and with pairwise comparison between them I have been able to get the DGE genes for each comparison.
I have two questions:

1) I ran the DGE analysis with and without the low count reads filter. When I did not use a filter, I obtained thousand of DGE genes and I could only use a P<0.0001 in order to get a reasonable number to take a look. When I filter the low count reads, as in one of the case studies in the manual, I selected 100cpm in the 3 replicates I have, as cutoff. In this case, with a P value of 0.05 I got few genes from 30-75, depending on the comparison.
I am a little bit worried that for a global gene expression analysis, this number is too low. Does anyone used a different cutoff for the filtering? Should I try 50 cpm?

2) I am a little bit confused on how the FC is calculated. Is the log2 and the cutoff is FC>2 fold?

Thanks for the help, I really appreciate your help


 -- output of sessionInfo(): 

R version 2.15.1 (2012-06-22)
Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

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

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