I am using DESeq to detect genes that are differentially expressed (DE). I am analyzing RNA-seq data from 6 samples, each of which belong to different class with no biological replicates – this is a poor experimental design as you noted in the DESeq vignette, but this is all I have. What I am finding it to be odd is that the number of DE genes I get from doing the pair-wise DE detection for 6 samples does not negatively correlate with the Pearson or Spearman correlation coefficient that I calculated pairwise amongst these 6 samples (I.e. I expected that libraries with the higher correlation coefficient would have less number of DE genes. But this is not what I am seeing.). I am looking for your insight and was wondering if what DESeq is doing to detect DE genes may explain what I am observing. Thank you. [[alternative HTML version deleted]]

Hi On 2011-07-20 17:24, Elizabeth Chun wrote: > I am using DESeq to detect genes that are differentially > expressed (DE). I am analyzing RNA-seq data from 6 samples, each of > which belong to different class with no biological replicates ? this is > a poor experimental design as you noted in the DESeq vignette, but this > is all I have. > What I am finding it to be odd is that the number of DE genes I get from > doing the pair-wise DE detection for 6 samples does not negatively > correlate with the Pearson or Spearman correlation coefficient that I > calculated pairwise amongst these 6 samples (I.e. I expected that > libraries with the higher correlation coefficient would have less number > of DE genes. But this is not what I am seeing.). > > I am looking for your insight and was wondering if what DESeq is doing > to detect DE genes may explain what I am observing. As explained in the vignette, DESeq's blind mode assumes that most genes are not differentially expressed. It will hence call only those few genes as DE that show differences much large than what is seen for most genes. The value of a correlation coefficient, however, will be chiefly dtermined by what all these many "typical" genes do that are not deemed DE. So, while the number of DE genes reported by DESeq in blind mode is the number of genes deemed atypical, the correlation coefficient reflects the magnitude of differences between typical genes. Clearly, these two numbers can vary quite independently, and don't need to show correlation. Simon