How to extract essential genes from enriched pathways (essGene) using DEseq2/GAGE workflow?

Question

[Ml6237]

Hello,

I have been conducting pathway analysis on my RNA-seq data using the Deseq2/GAGE workflow. I ran GAGE and it worked well generating a list of affected pathways. I used “KO” annotations from kegg.gsets (species=”ko”) as I am working on a non-model organism. I am now trying to extract data for essential member genes in my enriched pathways with essGene() However, I keep getting the error message “Error in expdata[rownames(b)[sel], ] : incorrect number of dimensions”. Is this possibly because my input data is not a column for each sample as demonstrated for microarray data in the 2009 GAGE vignette but a vector of 1 set of pairwise log2fold changes generated by Deseq2? However, from the more recent RNA-seq GAGE vignette, GAGE does run with pairwise log fold changes from DEseq2 by setting "ref=NULL" and "sample=NULL". I thought I'd apply the same method to using essGene() by also setting "ref" and "sample" to null, but unfortunately this did not work. Any advice on resolving this issue would be much appreciated, thanks.

Format of my data “deseq2.fc”- a vector with KO gene IDs as names and pairwise log2fold expression values:

Named num [1:5638] -0.0456 -0.2300 0.4829 -0.6356 0.6871 ...

 - attr(*, "names")= chr [1:5638] "K03598" "K12035" "K03556" "K16740"….

The code I used:

gageres <- gage(deseq2.fc, gsets= kegg.ko, ref=NULL, samp=NULL)

rownames(gageres$greater)[1:3]

gs=unique(unlist(kegg.ko[rownames(gageres$greater)[1:3]]))

str(gs)

chr [1:1176] "K00234" "K00235" "K00236" "K00237" ...

# Everything seems to work up until this point below:

essData=essGene(gs, deseq2.fc, ref=NULL, samp=NULL)

Error in expdata[rownames(b)[sel], ] : incorrect number of dimensions 

traceback()
1: essGene(gs, deseq2.fc, ref = NULL, samp = NULL)

[jgrant]

I am commenting because I'm having the same problem. Can someone help?

Answer 1

[konsta.kukkonen]

This is a problem specific to case where there's only one significant gene set, (so the esset.grp() does not return results) but you still want to get genes contributing to enrichment. It was pretty easy to fix, but in case someone else stumbles upon it:

The error message comes from argument exprs provided in a wrong form. There is a function called gagePrep() that converts exprs to right form. Provide that to essGene()

-Konsta