clusterProfiler包

分析

clusterprofiler简介.png
clusterProfiler-diagram.png

enrichGO.png
GO 输入数据.png
GOprofiler输出结果.png

输入数据：富集分析基因列表
输出数据：富集结果
输出结果：go.RData

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# 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")

enrichKEGG.png
KEGGj结果.png

输出数据：富集结果
输出结果：kegg.RData

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# 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) %>%
        setReadable(OrgDb = org.Hs.eg.db, keyType="ENTREZID")



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

可视化

barplot.png

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barplot(go, showCategory = 20, color = "pvalue")

dotplot.png

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dotplot(go, showCategory =20, color = "pvalue")

cnetplot.png

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cnetplot(kegg, circular = T, colorEdge = T)

heatplot.png

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heatplot(go) #   可添加差异倍数，增加色彩

emapplot.png
goplot.png

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emapplot(pairwise_termsim(go))

upsetplot.png

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upsetplot(go)