基因功能注释一言以概之，就是symbol--->ENTREZID--->GO/KEGG/GSEA。
第一步：加载包
library(DOSE)

library(GO.db)

library(org.Hs.eg.db)

library(topGO)

library(GSEABase)

library(clusterProfiler)

没安装的请自行安装

第二步：symbol--->ENTREZID

###上调基因注释

gene <- resSig_up$symbol

gene = bitr(gene, fromType="SYMBOL", toType="ENTREZID", OrgDb="org.Hs.eg.db")

org.Hs.eg.db是symbol转换成ENTREZID所依据的数据库，ENTREZID关联着很多文献数据，为后面的功能注释提供线索，所以需要ID转换。

第三步：GO和KEGG注释

###细胞组分

ego_CC <- enrichGO(gene = gene$ENTREZID,

OrgDb= org.Hs.eg.db,

ont = "CC",

pAdjustMethod = "BH",

minGSSize = 1,

pvalueCutoff = 0.01,

qvalueCutoff = 0.01,

readable = TRUE)

###生物过程

ego_BP <- enrichGO(gene = gene$ENTREZID,

OrgDb= org.Hs.eg.db,

ont = "BP",

pAdjustMethod = "BH",

minGSSize = 1,

pvalueCutoff = 0.01,

qvalueCutoff = 0.01,

readable = TRUE)

###分子功能：

ego_MF <- enrichGO(gene = gene$ENTREZID,

OrgDb= org.Hs.eg.db,

ont = "MF",

pAdjustMethod = "BH",

minGSSize = 1,

pvalueCutoff = 0.01,

qvalueCutoff = 0.01,

readable = TRUE)

pdf(file="ego_MF.pdf")

barplot(ego_MF, showCategory=20,title="EnrichmentGO_MF", drop=T)#条状图，按p从小到大排的

dev.off()

pdf(file="ego_BP.pdf")

dotplot(ego_BP,title="EnrichmentGO_BP_dot")#点图，按富集的数从大到小的

dev.off()

也可以一步到位：

go <- enrichGO(gene = gene$ENTREZID, OrgDb = org.Hs.eg.db, ont='ALL',

pAdjustMethod = 'BH',

pvalueCutoff = 0.01,

qvalueCutoff = 0.01,keyType = 'ENTREZID'

)

dim(go)

dim(go[go$ONTOLOGY=='BP',])

dim(go[go$ONTOLOGY=='CC',])

dim(go[go$ONTOLOGY=='MF',])

gbarplot(go,showCategory=20,drop=T)

dotplot(go,showCategory=50)

###KEGG分析

kk <- enrichKEGG(gene = gene$ENTREZID,

organism ="human",

pvalueCutoff = 0.01,

qvalueCutoff = 0.01,

minGSSize = 1,

#readable = TRUE ,

use_internal_data =FALSE)

pdf(file="barplot_kk.pdf")

barplot(kk)

dev.off()

pdf(file="dotplot_kk.pdf")

dotplot(kk)

dev.off()