Hi,

I have a dataset of RNASeq samples from 7 different regions. I am trying to see which genes are differentially expressed over all the regions.

When using the differential expression analysis of DESeq2 seems like it compares the differential expression between two conditions, whereas if I have 7 regions (conditions) A, B, C, D, E, F, G, I would like to know if there are significant expression changes on the individual gene transcriptions overall.

dds <- DESeq(dds) 
res <- results(dds)

log2 fold change (MLE): location A vs G 
Wald test p-value: location A vs G

I am using a vst normalised correction. And I have been told I should use the adjusted p-value for this. Is there a way where I can obtain a list of all the genes that are significant differentially expression across all regions?

Thanks

It sounds like you should be using an LRT of ~region vs ~1. Take a look at the vignette section on the Likelihood Ratio Test, and also see ?DESeq and ?results.