Hi, At first I'd like to explain that my RNAseq experiments involve RNAi depletions of RNA decay factors, so one should expect to see more upregulations. The libraries are ribodepleted, paired end and stranded. After mapping with tophat I use HTSeq/DESeq combo to discover DE genes (among tophat genes.gtf) Using raw counts I run DESeq on default settings and I get certain numer of signif. DE genes, approx. 1:1 up- to down-regulated. Everything seems fine though my MA plots are a bit skewed (example attached), there is a clear slope suggesting that more upregulation of genes of lower expression. Should I worry about this? I also tried to compare DESeq normalization with normalization to spike-ins present in the libraries, but the size factors assigned by DESeq seems much more accurate; although it's unclear why ? https://www.dropbox.com/s/lkq9clcc7nu8qma/analysis.pdf Finally, I turned to normalization that is not recommended by authors but some people do this: http://jura.wi.mit.edu/bio/education/hot_topics/rnaseq/ *rnaseqde_dec2011*.*pdf* Strangely, when I introduce pseudocounts, which in principal should not affect analyzes that much, they actually do. New upregulated hits appear and most downregulations disappear, importantly most of the upregulated enriched already existing clusters in GO. This suggests they may be real. Please note this is my second RNAseq analysis, so I'm really fresh and I would appreciate a lay explanation :) Cheers, Michael [[alternative HTML version deleted]]

did u removed the rRNA reads? try it shan