d = read.csv(your_csv_file) ## assume 1st column is ID ## 2nd column is FC ## feature 1: numeric vector geneList = d[,2] ## feature 2: named vector names(geneList) = as.character(d[,1]) ## feature 3: decreasing order geneList = sort(geneList, decreasing = TRUE)
library(msigdf) c2 <- msigdf.human %>% filter(category_code == "c2") %>% select(geneset, symbol) %>% as.data.frame library(clusterProfiler) data(geneList, package="DOSE") id = bitr(names(geneList), "ENTREZID", "SYMBOL", "org.Hs.eg.db") geneList = geneList[names(geneList) %in% id[,1]] names(geneList) = id[match(names(geneList), id[,1]), 2] de <- names(geneList)[1:100] x <- enricher(de, TERM2GENE = c2) y <- GSEA(geneList, TERM2GENE = c2) cnetplot(x, foldChange=geneList) gseaplot2(y, 1)
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