前面在讲GO和KEGG富集倍数（Fold Enrichment）如何计算时，给大家简单介绍过GO富集分析结果如何看。
ONTOLOGY：区分是BP，MF还是CC
ID：具体的GO条目的ID号
Description：GO条目的描述
GeneRatio：这里是一个分数，分子是富集到这个GO条目上的gene的数目，
分母是所有输入的做富集分析的gene的数目，可以是差异表达
分析得到的gene
BgRatio：Background Ratio. 这里也是一个分数，分母是人的所有编码蛋白的
基因中有GO注释的gene的数目，这里是19623个，分子是这19623个
gene中注释到这个GO条目上面的gene的数目
pvalue：富集的p值
p.adjust：校正之后的p值
qvalue：q值
geneID：输入的做富集分析的gene中富集到这个GO条目上面的具体的
gene名字
Count：输入的做富集分析的gene中富集到这个GO条目上面的gene的数目
有时候我们得到的富集结果中geneID这一列显示的是基因的名字（symbol），有时候显示的是一串数字（Entrez gene ID）或者是ensembl gene ID。其实我们最希望看到的是显示基因的名字（symbol），因为只有这样你才能一眼就看出是什么基因富集到这个GO条目或者是KEGG通路上，其他的ID号，都不太直观。那么我们如何能保证富集结果中就显示gene symbol呢？
今天给大家介绍三种不同的方法，来达到同样的效果假设我们这里差异表达分析得到了1000个差异表达的基因（DEG），基因的ID号是ensembl gene ID。
load("DEG.rds")
ls()
library(org.Hs.eg.db)
library(clusterProfiler)
ego <- enrichGO(gene = DEG,
OrgDb=org.Hs.eg.db,
ont = "all",
pAdjustMethod = "BH",
minGSSize = 10,
pvalueCutoff = 0.01,
qvalueCutoff = 0.01,
keyType='ENSEMBL')
富集得到的结果如下，geneID为ensembl gene ID
>ego
# over-representation test
#
#...@organism Homo sapiens
#...@ontology GOALL
#...@keytype ENSEMBL
#...@gene chr [1:1000] "ENSG00000259250" "ENSG00000255717" ...
#...pvalues adjusted by 'BH' with cutoff <0.01
#...81 enriched terms found
'data.frame': 81 obs. of 10 variables:
$ ONTOLOGY : Factor w/ 3 levels "BP","CC","MF": 1 1 1 1 1 1 1 1 1 1 ...
$ ID : chr "GO:0016054" "GO:0046395" "GO:0044282" "GO:0009063" ...
$ Description: chr "organic acid catabolic process" "carboxylic acid catabolic process" "small molecule catabolic process" "cellular amino acid catabolic process" ...
$ GeneRatio : chr "50/832" "50/832" "63/832" "30/832" ...
$ BgRatio : chr "300/20610" "300/20610" "476/20610" "140/20610" ...
$ pvalue : num 1.06e-17 1.06e-17 8.27e-17 4.25e-14 1.33e-11 ...
$ p.adjust : num 2.69e-14 2.69e-14 1.39e-13 5.38e-11 1.34e-08 ...
$ qvalue : num 2.51e-14 2.51e-14 1.30e-13 5.01e-11 1.25e-08 ...
$ geneID : chr "ENSG00000198650/ENSG00000248098/ENSG00000078070/ENSG00000169738/ENSG00000113492/ENSG00000113790/ENSG00000111271"| __truncated__ "ENSG00000198650/ENSG00000248098/ENSG00000078070/ENSG00000169738/ENSG00000113492/ENSG00000113790/ENSG00000111271"| __truncated__ "ENSG00000198650/ENSG00000248098/ENSG00000171903/ENSG00000173597/ENSG00000078070/ENSG00000169738/ENSG00000113492"| __truncated__ "ENSG00000198650/ENSG00000248098/ENSG00000078070/ENSG00000113492/ENSG00000008311/ENSG00000139631/ENSG00000140905"| __truncated__ ...
$ Count : int 50 50 63 30 50 35 24 22 27 43 ...
#...Citation
Guangchuang Yu, Li-Gen Wang, Yanyan Han and Qing-Yu He.
clusterProfiler: an R package for comparing biological themes among
gene clusters. OMICS: A Journal of Integrative Biology
2012, 16(5):284-287
方法一、使用readable = TRUE参数
ego1 <- enrichGO(gene = DEG,
OrgDb=org.Hs.eg.db,
ont = "all",
pAdjustMethod = "BH",
minGSSize = 10,
pvalueCutoff = 0.01,
qvalueCutoff = 0.01,
keyType='ENSEMBL',
readable = TRUE)
这时候得到的结果你会发现已经转换成了gene symbol
>ego1
# over-representation test
#
#...@organism Homo sapiens
#...@ontology GOALL
#...@keytype ENSEMBL
#...@gene chr [1:1000] "ENSG00000259250" "ENSG00000255717" ...
#...pvalues adjusted by 'BH' with cutoff <0.01
#...81 enriched terms found
'data.frame': 81 obs. of 10 variables:
$ ONTOLOGY : Factor w/ 3 levels "BP","CC","MF": 1 1 1 1 1 1 1 1 1 1 ...
$ ID : chr "GO:0016054" "GO:0046395" "GO:0044282" "GO:0009063" ...
$ Description: chr "organic acid catabolic process" "carboxylic acid catabolic process" "small molecule catabolic process" "cellular amino acid catabolic process" ...
$ GeneRatio : chr "50/832" "50/832" "63/832" "30/832" ...
$ BgRatio : chr "300/20610" "300/20610" "476/20610" "140/20610" ...
$ pvalue : num 1.06e-17 1.06e-17 8.27e-17 4.25e-14 1.33e-11 ...
$ p.adjust : num 2.69e-14 2.69e-14 1.39e-13 5.38e-11 1.34e-08 ...
$ qvalue : num 2.51e-14 2.51e-14 1.30e-13 5.01e-11 1.25e-08 ...
$ geneID : chr "TAT/BCKDHA/MCCC1/DCXR/AGXT2/EHHADH/ACAD10/ACADS/ACOX1/AASS/PCCB/CSAD/GCSH/AFMID/GPT/ABAT/MLYCD/ABHD10/PRODH2/DD"| __truncated__ "TAT/BCKDHA/MCCC1/DCXR/AGXT2/EHHADH/ACAD10/ACADS/ACOX1/AASS/PCCB/CSAD/GCSH/AFMID/GPT/ABAT/MLYCD/ABHD10/PRODH2/DD"| __truncated__ "TAT/BCKDHA/CYP4F11/SULT1B1/MCCC1/DCXR/AGXT2/PGM2L1/DPYD/DERA/EHHADH/ACAD10/ACADS/ACOX1/AASS/PCCB/CSAD/GCSH/AFMI"| __truncated__ "TAT/BCKDHA/MCCC1/AGXT2/AASS/CSAD/GCSH/AFMID/GPT/ABAT/PRODH2/DDAH1/ARG1/ACMSD/BCKDK/SHMT1/HGD/CDO1/DBT/GSTZ1/HSD"| __truncated__ ...
$ Count : int 50 50 63 30 50 35 24 22 27 43 ...
#...Citation
Guangchuang Yu, Li-Gen Wang, Yanyan Han and Qing-Yu He.
clusterProfiler: an R package for comparing biological themes among
gene clusters. OMICS: A Journal of Integrative Biology
2012, 16(5):284-287
方法二、使用setReadable函数
library(DOSE)
#如果原始的ID号为entrez gene id那么这里keyType设置为ENTREZID
ego2<-setReadable(ego, OrgDb = org.Hs.eg.db, keyType="ENSEMBL")
转换之后的结果为
>ego2
# over-representation test
#
#...@organism Homo sapiens
#...@ontology GOALL
#...@keytype ENSEMBL
#...@gene chr [1:1000] "ENSG00000259250" "ENSG00000255717" "ENSG00000163328" ...
#...pvalues adjusted by 'BH' with cutoff <0.01
#...81 enriched terms found
'data.frame': 81 obs. of 10 variables:
$ ONTOLOGY : Factor w/ 3 levels "BP","CC","MF": 1 1 1 1 1 1 1 1 1 1 ...
$ ID : chr "GO:0016054" "GO:0046395" "GO:0044282" "GO:0009063" ...
$ Description: chr "organic acid catabolic process" "carboxylic acid catabolic process" "small molecule catabolic process" "cellular amino acid catabolic process" ...
$ GeneRatio : chr "50/832" "50/832" "63/832" "30/832" ...
$ BgRatio : chr "300/20610" "300/20610" "476/20610" "140/20610" ...
$ pvalue : num 1.06e-17 1.06e-17 8.27e-17 4.25e-14 1.33e-11 ...
$ p.adjust : num 2.69e-14 2.69e-14 1.39e-13 5.38e-11 1.34e-08 ...
$ qvalue : num 2.51e-14 2.51e-14 1.30e-13 5.01e-11 1.25e-08 ...
$ geneID : chr "TAT/BCKDHA/MCCC1/DCXR/AGXT2/EHHADH/ACAD10/ACADS/ACOX1/AASS/PCCB/CSAD/GCSH/AFMID/GPT/ABAT/MLYCD/ABHD10/PRODH2/DD"| __truncated__ "TAT/BCKDHA/MCCC1/DCXR/AGXT2/EHHADH/ACAD10/ACADS/ACOX1/AASS/PCCB/CSAD/GCSH/AFMID/GPT/ABAT/MLYCD/ABHD10/PRODH2/DD"| __truncated__ "TAT/BCKDHA/CYP4F11/SULT1B1/MCCC1/DCXR/AGXT2/PGM2L1/DPYD/DERA/EHHADH/ACAD10/ACADS/ACOX1/AASS/PCCB/CSAD/GCSH/AFMI"| __truncated__ "TAT/BCKDHA/MCCC1/AGXT2/AASS/CSAD/GCSH/AFMID/GPT/ABAT/PRODH2/DDAH1/ARG1/ACMSD/BCKDK/SHMT1/HGD/CDO1/DBT/GSTZ1/HSD"| __truncated__ ...
$ Count : int 50 50 63 30 50 35 24 22 27 43 ...
#...Citation
Guangchuang Yu, Li-Gen Wang, Yanyan Han and Qing-Yu He.
clusterProfiler: an R package for comparing biological themes among
gene clusters. OMICS: A Journal of Integrative Biology
2012, 16(5):284-287
方法三、自己动手丰衣足食
library(org.Hs.eg.db)
ego3=as.data.frame(ego)
ensembl=strsplit(ego3$geneID,"/")
symbol=sapply(ensembl,function(x){
y=bitr(x, fromType="ENSEMBL", toType="SYMBOL", OrgDb="org.Hs.eg.db")
#一对多，取第一个
y=y[!duplicated(y$ENSEMBL),-1]
y=paste(y,collapse = "/")
})
ego3$geneID=symbol
ego3
得到结果如下
参考下面文章获取DEG.rds文件
GO和KEGG富集结果如何显示基因symbol