After DESeq2 analysis of my RNAseq data in order to obtain differentially expressed genes between 2 cell types, I have a csv file with approximatelly 26000 genes, of which around 6000 genes are differentially expressed (padjustedvalue < 0.05). Now I want to use goseq in order to study pathways.
I am a very amateur R user and I am starting to learn about all this, so I have no idea what I have to do now. By checking this website http://www.bioconductor.org/packages/release/bioc/vignettes/goseq/inst/doc/goseq.pdf, I understand that I have to create 2 vectors, one with all my genes, and other with the DEGs. After that, I get lost. What I have done until now in order to create the vectors is the following, although I am not sure if it is correct:
d <- read.csv("myfile.csv", header=T, row.names=1)
all_genes <- row.names(d)
DE_genes <- all_genes[which(d$padj<0.05)]
I will really appreciate if someone can give me the scrips/code in order to do goseq analysis, starting from my file.csv with all the genes.