Introduction | Biomedical Knowledge Mining using GOSemSim and clusterProfiler (yulab-smu.top)
部分使用
#GO classification
library(clusterProfiler)
data(geneList, package="DOSE")
gene <- names(geneList)[abs(geneList) > 2]
# Entrez gene ID
head(gene)
ggo <- groupGO(gene = gene,
OrgDb = org.Hs.eg.db,
ont = "CC",
level = 3,
readable = TRUE)
head(ggo)
##############################################################
##KEGG##
library(clusterProfiler)
search_kegg_organism('ece', by='kegg_code')
ecoli <- search_kegg_organism('Escherichia coli', by='scientific_name')
dim(ecoli)
data(geneList, package="DOSE")
gene <- names(geneList)[abs(geneList) > 2]
kk <- enrichKEGG(gene = gene,
organism = 'hsa',
pvalueCutoff = 0.05)
head(kk)
【精选】RNA 11. SCI 文章中基因表达富集之 GSEA_gsea数据库-CSDN博客