Hi, I am trying this workflow. I am wondering for pathway analysis in part 6.1 DESeq2, how should I change it to make the kegg data suitable for s.pombe. The scripts are for human as they are. The codes follow as:
require(gage)
data(kegg.gs)
fc.kegg.p <- gage(exp.fc, gsets = kegg.gs, ref = NULL, samp = NULL)
sel <- fc.kegg.p$greater[, "q.val"] < 0.1 & !is.na(fc.kegg.p$greater[, "q.val"])
path.ids <- rownames(fc.kegg.p$greater)[sel]
sel.l <- fc.kegg.p$less[, "q.val"] < 0.1 & !is.na(fc.kegg.p$less[,"q.val"])
path.ids.l <- rownames(fc.kegg.p$less)[sel.l]
path.ids2 <- substr(c(path.ids, path.ids.l), 1, 8)
require(pathview)
#view first 3 pathways as demo
pv.out.list <- sapply(path.ids2[1:3], function(pid) pathview(
gene.data = exp.fc, pathway.id = pid,
species = "hsa", out.suffix=out.suffix))
Please help me with this!
One good idea would be to ask the author of the original work. Another, would be to break down your problem into smaller pieces, and to ask people here, one step at a time. I am not sure that someone would invest time and effort to debug the _whole_ thing for you. Sorry.
It's not actually as complex as it looks; see my answer.