Hello community and in special to M Love,
thank you for the support what you give trough this platform, I'm sure you have improved a lot the performance of RNAseq and corrected several fails.
I have read about the "problematic" around low count genes and DESeq2, I found several post here in the support forum and I'm quite sure about have understood you. If I'm right you mentioned several times the very good performance of independent filtering step and the basis of "genefilter" behind it.
However, just to clarify one specific problem, if I have some contamination in my samples coming for example from the digestive content (diets are different between studied groups) some people warm me about they shouldn't appear (even when they are actually here) because the proportion of reads coming from my sample and from the contaminants make them to have a low coverage so I should filter out these genes with low counts assigned (sorry that's a awful sentence construction).
In contrast, I found you highlighting the risk to take out low read count genes and how good is the pipeline dealing with it.
Of course I'm quite confident about follow your advices but just to avoid argue with my supervisor, the argument which support that is the independent filtering or there are something more that I'm missing?
Thank you for your time and sorry about this (maybe) awkward consult
Pablo
Thanks for that! The plot looks very strange..https://ibb.co/gARrh6
Well you can see why it picks a high filter. You can disable this if it’s not desired.