clusterProfiler包

泡泡2023-06-052023-07-19

分析

clusterprofiler简介.png

GO 输入数据.png
GOprofiler输出结果.png

# load packages -----------------------------------------------------------

library(clusterProfiler)
library(org.Bt.eg.db)
library(readxl)

# load data ---------------------------------------------------------------

rna <- read_xlsx("gene.xlsx")
SYMBOL <- unique(rna$geneSymbol)
rna <- data.frame(SYMBOL)

# Id transition -----------------------------------------------------------

gene.list <- bitr(rna$SYMBOL,
                fromType = "SYMBOL",
                toType = "ENTREZID",
                OrgDb = org.Bt.eg.db)
head(gene.list)


# prepare analysis --------------------------------------------------------

gene <- gene.list$ENTREZID

# GO analysis -------------------------------------------------------------

go <- enrichGO(gene = gene,
               OrgDb = org.Bt.eg.db,
               keyType = "ENTREZID",
               ont = 'ALL',
               pvalueCutoff = 0.05,
               pAdjustMethod = 'BH',
               qvalueCutoff = 0.05,
               minGSSize = 10,
               maxGSSize = 500,
               readable = T,
               pool = F)


# Output the result -------------------------------------------------------

write.csv(go@result, file = "go_enrichresults.csv")
save(go, file = "go.RData")

KEGGj结果.png

输出数据：富集结果
 输出结果：kegg.RData

# kegg analysis -----------------------------------------------------------

# 接GO富集分析的数据进行分析

kegg <- enrichKEGG(gene = gene,
                   organism = "bta",
                   pvalueCutoff = 0.05,
                   pAdjustMethod = "BH",
                   minGSSize = 10,
                   maxGSSize = 500,
                   qvalueCutoff = 0.2,
                   use_internal_data = F)


# Output the KEGG result --------------------------------------------------
write.csv(kegg@result, file = "kegg_enrichresults.csv")