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 -- Sent via the guest posting facility at bioconductor.org.

> Date: Wed, 21 Nov 2012 11:23:55 -0800 (PST) > From: "Vittoria Roncalli [guest]" <guest at="" bioconductor.org=""> > To: bioconductor at r-project.org, roncalli at hawaii.edu > Subject: [BioC] > > > 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. It's a good idea to follow the advice in the User's Guide. > I am a little bit worried that for a global gene expression analysis, > this number is too low. There is no such thing as too many or two many DE genes. The whole purpose of an analysis to find out the truth, whatever that might be. > Does anyone used a different cutoff for the filtering? Should I try 50 > cpm? Without knowing your sequencing depth, how can we tell? Why not follow advice in the User's Guide? > 2) I am a little bit confused on how the FC is calculated. Is the log2 and the cutoff is FC>2 fold? Please read the documentation. > 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 The session information is supposed to be from your edgeR analysis session. Otherwise it gives us no information. Gordon ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}