之前写的富集分析可视化代码，之前是可以正常运行的，为什么这次运行绘制气泡图的代码时会失败？
# ====================== 6. 模块3：GO富集分析（原逻辑无修改） ======================
write_log("========== 开始：GO富集分析（生物过程BP+细胞组分CC+分子功能MF） ==========")
write_log(paste("富集分析筛选阈值：p<", threshold$adj_pval, "，q<", threshold$adj_pval))
check_files(c("diff.txt")) # 检查差异基因文件是否存在
# 6.1 读取差异基因并转换为Entrez ID（clusterProfiler要求）
rt <- read.table("diff.txt", header = T, sep = "\t", check.names = F)
genes <- as.vector(rt[,1])
write_log(paste("输入GO富集分析的差异基因数：", length(genes)))
# 基因名→Entrez ID转换
entrezIDs <- as.character(mget(genes, org.Hs.egSYMBOL2EG, ifnotfound = NA))
gene <- entrezIDs[entrezIDs != "NA"]
na_gene <- sum(is.na(entrezIDs))
write_log(paste("基因名→Entrez ID转换：有效ID数", length(gene), "，无效/未注释ID数", na_gene))
if(length(gene)==0){
write_log("错误：无有效Entrez ID，GO富集分析终止！")
stop("无有效Entrez ID，无法进行GO富集分析")
}
# 6.2 GO富集分析（全本体：BP+CC+MF）
kk <- enrichGO(gene = gene, OrgDb = org.Hs.eg.db, pvalueCutoff = 1, qvalueCutoff = 1,
ont = "all", readable = T) # 先不筛选，后续统一过滤
GO <- as.data.frame(kk)
# 筛选显著富集的GO条目
GO_sig <- GO[(GO$pvalue<threshold$adj_pval & GO$qvalue<threshold$adj_pval),]
write.table(GO_sig, file = "GO.txt", sep = "\t", quote = F, row.names = F)
write_log(paste("GO富集分析总条目数：", nrow(GO), "，显著富集条目数：", nrow(GO_sig)))
if(nrow(GO_sig)==0){
write_log(paste("警告：无显著富集的GO条目（p<", threshold$adj_pval, ", q<", threshold$adj_pval, "），跳过GO可视化"))
}else{
write_log(paste("输出GO显著富集结果：GO.txt（含本体、描述、基因数、p值、q值、核心基因）"))
# 6.3 定义展示条目数（不足5个则展示全部）
showNum <- if(nrow(GO_sig)<5) nrow(GO_sig) else 5
colorSel <- if(threshold$adj_pval>0.05) "pvalue" else "qvalue" # 颜色依据：q值优先
# 6.4 绘制GO可视化图：柱状图+气泡图（分本体展示）
# 柱状图（展示富集因子）
pdf(file = "GObarplot.pdf", width = 12, height = 12)
print(barplot(kk, drop = TRUE, showCategory = showNum, split = "ONTOLOGY", color = colorSel) +
facet_grid(ONTOLOGY~., scale = 'free'))
dev.off()
# 气泡图（展示基因数+富集因子）
pdf(file = "GObubble.pdf", width = 12, height = 12)
bub = dotplot(kk, showCategory = showNum, orderBy = "GeneRatio", split = "ONTOLOGY", color = colorSel) + facet_grid(ONTOLOGY~., scale = 'free')
print(bub)
dev.off()
# 6.5 绘制GO圈图+聚类图（展示基因与GO条目的关联）
go <- data.frame(Category=GO_sig$ONTOLOGY, ID=GO_sig$ID, Term=GO_sig$Description,
Genes = gsub("/", ", ", GO_sig$geneID), adj_pval = GO_sig$p.adjust)
genelist <- data.frame(ID=rt$id, logFC=rt$logFC); row.names(genelist)=genelist[,1]
circ <- circle_dat(go, genelist)
# 定义展示数（不足则展示全部）
termNum <- if(nrow(go)<8) nrow(go) else 8
geneNum <- if(nrow(genelist)<200) nrow(genelist) else 200
chord <- chord_dat(circ, genelist[1:geneNum,], go$Term[1:termNum])
# 圈图（基因-GO条目关联）
pdf(file="GOcircos.pdf", width=10, height=10)
GOChord(chord, space = 0.001, gene.order = 'logFC', gene.space = 0.25,
gene.size = 5, border.size = 0.1, process.label = 6)
dev.off()
# 聚类图（基因表达与GO条目聚类）
pdf(file="GOcluster.pdf",width=12, height=10)
GOCluster(circ, go$Term[1:termNum], lfc.space = 0.2, lfc.width = 1,
term.space = 0.2, term.width = 1)
dev.off()
write_log(paste("绘制GO富集圈图：GOcircos.pdf（展示前", termNum, "个GO条目与", geneNum, "个基因的关联）"))
write_log(paste("绘制GO富集聚类图：GOcluster.pdf（展示基因logFC与GO条目的聚类关系）"))
}
write_log("========== 完成：GO富集分析 ==========\n")
