零基础入门转录组数据分析——GO+KEGG富集分析

# 安装并加载必要的包
if (!requireNamespace("org.Hs.eg.db", quietly = TRUE)) {
    install.packages("org.Hs.eg.db")
}
if (!requireNamespace("clusterProfiler", quietly = TRUE)) {
    install.packages("clusterProfiler")
}
if (!requireNamespace("enrichplot", quietly = TRUE)) {
    install.packages("enrichplot")
}
library(org.Hs.eg.db)
library(clusterProfiler)
library(enrichplot)

# 读取转录组数据和基因型
count_data <- read.csv("gene_counts.csv", row.names = 1)
group_list <- read.csv("sample_groups.csv", header = TRUE, row.names = 1)

# 进行GO和KEGG富集分析
ego_results <- enrichGO(count_data, "org.Hs.eg.db", keyType = "ENTREZID",
                        pvalueCutoff = 0.05, qvalueCutoff = 0.05)
kegg_results <- enrichKEGG(count_data, organism = "hsa", pvalueCutoff = 0.05, qvalueCutoff = 0.05)

# 绘制富集通路图
dotplot(ego_results)

# 进行富集分析并绘制条形图
barplot(ego_results)

# 进行富集分析并绘制热图
heatplot(ego_results)

# 绘制KEGG MAP的富集通路图
plotKeggMap(kegg_results, count_data)