模式物种GO富集分析

模式物种进行GO富集分析绘图

     今天通过clusterProfiler包对模式物种进行GO富集分析，并绘制富集分析图片,今天以小鼠数据为例进行，代码如下：

1. 安装所需的R包

Install.packages(“BiocManager”)

Install.packages(“clusterProfiler”)

Install.packages(“ggplot2”)

Install.packages(“tidyverse”)

2.导入所需的R包

library(clusterProfiler)

library(ggplot2)

1. 差异分析结果文件

2. 富集分析

#读取小鼠基因差异分析结果数据

gsym.fc <- read.csv("easy_input_Mm.csv", as.is = T)

#获取基因名与ENTREZID的对应关系。

gsym.id <- bitr(gsym.fc$SYMBOL, #基因名

                fromType = "SYMBOL", #从gene symbol

                toType = "ENTREZID", #提取ENTREZ ID

                OrgDb = "org.Mm.eg.db") #相应物种

idvec <- gsym.id$ENTREZID

names(idvec) <- gsym.id$SYMBOL

gsym.fc$ENTREZID <- idvec[gsym.fc$SYMBOL]

write.csv(gsym.fc[,c(3,2)], "very_easy_input_Mm.csv", quote = F, row.names = F)

id.fc <- read.csv("very_easy_input_Mm.csv", as.is = T)

#enrich进行富集分析

ego <- enrichGO(gene = id.fc$ENTREZID,

                #小鼠用这行

                OrgDb = org.Mm.eg.db,

                #人类用这行

                #OrgDb = org.Hs.eg.db,

                #非模式生物用这行，例如玉米

                #OrgDb = maize.db,

                ont = "BP", #或MF或CC

                pAdjustMethod = "BH",

                #pvalueCutoff  = 0.001,

                qvalueCutoff  = 0.01)

write.csv(ego,"enrichGO_output.csv",quote = F)

egox <- setReadable(ego, 'org.Mm.eg.db', #物种

                    'ENTREZID')

geneList <- id.fc$log2fc

names(geneList)<- gsym.fc$SYMBOL

#绘制圈图，通过circular来确定。

cnetplot(egox,

         foldChange = geneList,

         #foldChange = NULL, #不展示倍数

         circular = TRUE,

         #node_label = FALSE, #如果太多，就不要显示基因名了

         showCategory = 4, #显示富集的term数量，默认5

         colorEdge = TRUE)

ggsave("clusterProfiler_circle.pdf", width = 8, height = 5)

cnetplot(egox,

         foldChange = geneList,

         #foldChange = NULL, #不展示倍数

         #circular = TRUE,

         #node_label = FALSE, #不显示基因名

         showCategory = 4, #显示的富集term数量，默认5

         colorEdge = TRUE)

ggsave("clusterProfiler_not_circle.pdf", width = 8, height = 5)

3. Go富集分析结果