Making sense of RNA-seq comparisons

***Hey, it's RRResearch's 10th blogiversary!***

Back to work:

I'm working on the toxin-antitoxin manuscript, and trying to use the RNA-seq data to decide which genes have changed expression in which mutants.  This information should help us understand how the toxin acts to prevent DNA uptake, and what else it might affect.

The comparisons should be straightforward because the former undergrad/summer student left me with a superb set of analyses and R scripts, including EdgeR and DESeq2 analyses comparing expression of different strains at the various time points.  But I'm having a hard time making sense of the results, because some comparisons that I expect to give few significant differences give many, and others give very few.

There are also big inconsistencies between the EdgeR and DESeq2 results.  For example, in one comparison of two mutant strains (taxx vs antx, at time M1), EdgeR finds no genes that are significantly different but DESeq2 finds about 70 genes, with a cutoff for 'significant' that requires both of the following:
  1. must have padj or FDR score less than 0.05<0 .05="" li="">
  2. must have at least a twofold change in expression
In fact, all but two of the genes in this EdgeR comparison have FDR values greater than 0.5, and almost all have FDR values of 1.00.


I had a Skype conversation with the former post-doc this morning, and he suggested an analysis that might clear things up for me.  But I'll need to ask the former student to do it for me, or to modify the R scripts so I can do it.

Step 1:  Identify all the genes whose expression is significantly changed at each of the MIV timepoints (M1, M2 and M3), relative to their expression in log phase in sBHI (M0 timepoint).

Step 2:  Using the same cutoff, examine the genes that differ significantly between different strains at a single time point.  How many of these are also among the 'MIV-induced' set for this timepoint?

If we find that a particular genetic difference (wildtype vs a mutant, or two mutants vs each other) causes changes in the same genes that are changed by MIV in wildtype cells, we could conclude that the genetic difference affects the cellular response to MIV.  If there's no more overlap than we'd expect by chance, then no.

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