Hello everyone,

I am using DESeq2 to analyse some bulk RNAseq data. I cannot get my head around what the betaPrior argument is doing in the dds() function.

The documentation is "whether or not to put a zero-mean normal prior on the non-intercept coefficients See nbinomWaldTest for description of the calculation of the beta prior. By default, the beta prior is used only for the Wald test, but can also be specified for the likelihood ratio test", does not make any sense to me.

Changing between true and false seems to affect the results quite a bit (51 vs. 29 DE genes).

Would anyone please be able to give a concise explanation of what it is doing (considering my relatively weak statistical background) and a few examples of when choosing it is important?

Thanks in advance

Those DE genes - is that after a log fold change cut off?