### R code from vignette source 'pathview.Rnw' ################################################### ### code chunk number 1: synopsis1 (eval = FALSE) ################################################### ## library(pathview) ## data(gse16873.d) ## pv.out <- pathview(gene.data = gse16873.d[, 1], pathway.id = "04110", ## species = "hsa", out.suffix = "gse16873") ################################################### ### code chunk number 2: install (eval = FALSE) ################################################### ## if (!requireNamespace("BiocManager", quietly=TRUE)) ## install.packages("BiocManager") ## BiocManager::install("pathview") ################################################### ### code chunk number 3: 0.5] pv.out <- pathview(gene.data = sel.genes, cpd.data = sel.cpds, pathway.id = demo.paths$sel.paths[i], species = "hsa", out.suffix = "sel.genes.sel.cpd", keys.align = "y", kegg.native = T, key.pos = demo.paths$kpos1[i], limit = list(gene = 5, cpd = 2), bins = list(gene = 5, cpd = 2), na.col = "gray", discrete = list(gene = T, cpd = T)) pv.out <- pathview(gene.data = sel.genes, cpd.data = sim.cpd.data, pathway.id = demo.paths$sel.paths[i], species = "hsa", out.suffix = "sel.genes.cpd", keys.align = "y", kegg.native = T, key.pos = demo.paths$kpos1[i], limit = list(gene = 5, cpd = 1), bins = list(gene = 5, cpd = 10), na.col = "gray", discrete = list(gene = T, cpd = F)) ################################################### ### code chunk number 29: gene.ensprot_cpd.cas ################################################### cpd.cas <- sim.mol.data(mol.type = "cpd", id.type = cpd.simtypes[2], nmol = 10000) gene.ensprot <- sim.mol.data(mol.type = "gene", id.type = gene.idtype.list[4], nmol = 50000) pv.out <- pathview(gene.data = gene.ensprot, cpd.data = cpd.cas, gene.idtype = gene.idtype.list[4], cpd.idtype = cpd.simtypes[2], pathway.id = demo.paths$sel.paths[i], species = "hsa", same.layer = T, out.suffix = "gene.ensprot.cpd.cas", keys.align = "y", kegg.native = T, key.pos = demo.paths$kpos2[i], sign.pos = demo.paths$spos[i], limit = list(gene = 3, cpd = 3), bins = list(gene = 6, cpd = 6)) ################################################### ### code chunk number 30: gene.ensprot_cpd.cas.manual.map ################################################### id.map.cas <- cpdidmap(in.ids = names(cpd.cas), in.type = cpd.simtypes[2], out.type = "KEGG COMPOUND accession") cpd.kc <- mol.sum(mol.data = cpd.cas, id.map = id.map.cas) id.map.ensprot <- id2eg(ids = names(gene.ensprot), category = gene.idtype.list[4], org = "Hs") gene.entrez <- mol.sum(mol.data = gene.ensprot, id.map = id.map.ensprot) pv.out <- pathview(gene.data = gene.entrez, cpd.data = cpd.kc, pathway.id = demo.paths$sel.paths[i], species = "hsa", same.layer = T, out.suffix = "gene.entrez.cpd.kc", keys.align = "y", kegg.native = T, key.pos = demo.paths$kpos2[i], sign.pos = demo.paths$spos[i], limit = list(gene = 3, cpd = 3), bins = list(gene = 6, cpd = 6)) ################################################### ### code chunk number 31: korg ################################################### data(korg) head(korg) #number of species which use Entrez Gene as the default ID sum(korg[,"entrez.gnodes"]=="1",na.rm=T) #number of species which use other ID types or none as the default ID sum(korg[,"entrez.gnodes"]=="0",na.rm=T) #new from 2017: most species which do not have Entrez Gene annotation any more na.idx=is.na(korg[,"ncbi.geneid"]) sum(na.idx) ################################################### ### code chunk number 32: bods_gene.idtype.list ################################################### data(bods) bods data(gene.idtype.list) gene.idtype.list ################################################### ### code chunk number 33: eco.dat.kegg ################################################### eco.dat.kegg <- sim.mol.data(mol.type="gene",id.type="kegg",species="eco",nmol=3000) head(eco.dat.kegg) pv.out <- pathview(gene.data = eco.dat.kegg, gene.idtype="kegg", pathway.id = "00640", species = "eco", out.suffix = "eco.kegg", kegg.native = T, same.layer=T) ################################################### ### code chunk number 34: eco.dat.kegg ################################################### eco.dat.entrez <- sim.mol.data(mol.type="gene",id.type="entrez",species="eco",nmol=3000) head(eco.dat.entrez) pv.out <- pathview(gene.data = eco.dat.entrez, gene.idtype="entrez", pathway.id = "00640", species = "eco", out.suffix = "eco.entrez", kegg.native = T, same.layer=T) ################################################### ### code chunk number 35: eco.dat.symbol (eval = FALSE) ################################################### ## egid.eco=eg2id(names(eco.dat.entrez), category="symbol", pkg="org.EcK12.eg.db") ## eco.dat.symbol <- eco.dat.entrez ## names(eco.dat.symbol) <- egid.eco[,2] ## head(eco.dat.kegg) ## pv.out <- pathview(gene.data = eco.dat.symbol, gene.idtype="symbol", ## pathway.id = "00640", species = "eco", out.suffix = "eco.symbol.2layer", ## kegg.native = T, same.layer=F) ################################################### ### code chunk number 36: gene.ensprot_cpd.cas.manual.map ################################################### ko.data=sim.mol.data(mol.type="gene.ko", nmol=5000) pv.out <- pathview(gene.data = ko.data, pathway.id = "04112", species = "ko", out.suffix = "ko.data", kegg.native = T) ################################################### ### code chunk number 37: GAGE.Pathview.pipeline (eval = FALSE) ################################################### ## library(gage) ## data(gse16873) ## cn <- colnames(gse16873) ## hn <- grep('HN',cn, ignore.case =TRUE) ## dcis <- grep('DCIS',cn, ignore.case =TRUE) ## data(kegg.gs) ## #pathway analysis using gage ## gse16873.kegg.p <- gage(gse16873, gsets = kegg.gs, ## ref = hn, samp = dcis) ## #prepare the differential expression data ## gse16873.d <- gagePrep(gse16873, ref = hn, samp = dcis) ## #equivalently, you can do simple subtraction for paired samples ## gse16873.d <- gse16873[,dcis]-gse16873[,hn] ## #select significant pathways and extract their IDs ## sel <- gse16873.kegg.p$greater[, "q.val"] < 0.1 & !is.na(gse16873.kegg.p$greater[, ## "q.val"]) ## path.ids <- rownames(gse16873.kegg.p$greater)[sel] ## path.ids2 <- substr(path.ids[c(1, 2, 7)], 1, 8) ## #pathview visualization ## pv.out.list <- sapply(path.ids2, function(pid) pathview(gene.data = gse16873.d[, ## 1:2], pathway.id = pid, species = "hsa"))