【画图】如何预测基因的功能？

lungTMP<-read.csv("Lung.csv",header = T,check.names = F,row.names = 1)

ACE2geneexp<-data.frame(t(lungTMP[str_sub(rownames(lungTMP),end=15)==gene,]),check.names = F)
ACE2geneexp$group<-ifelse(ACE2geneexp$ENSG00000130234.10 > median(ACE2geneexp$ENSG00000130234.10),"high","low")
ACE2geneexp$group<-as.factor(ACE2geneexp$group)

library(limma)
design<-model.matrix(~0+group)
contrast.matrix <- makeContrasts (contrasts = c("grouphigh-grouplow"), levels = design)
fit1 <- contrasts.fit(lmFit(lungTMP, design), contrast.matrix)
fit2 <- eBayes(fit1)
dif <- topTable(fit2,coef="grouphigh-grouplow",n=nrow(fit2),adjust="BH",sort.by = "P")

library(clusterProfiler)
library(org.Hs.eg.db)
library(ggplot2)
library(annoE)
genecluster<-AnnoENSG(EntrezID = T,data=dif )
genecluster<-genecluster[order(genecluster$logFC,decreasing = T),]
gene<-genecluster$EntrezGene
genelist<-genecluster$logFC
names(genelist)<-gene
ego <- enrichGO(gene          = gene,
                ont           = "ALL",
                OrgDb         = org.Hs.eg.db,
                pAdjustMethod = "BH",
                pvalueCutoff  = 0.05,
                qvalueCutoff  = 0.05,
                readable      = TRUE)
go.plot<-dotplot(ego, showCategory = 10,split="ONTOLOGY")+ facet_grid(ONTOLOGY~., scale="free")
go.plot

emapplot(ego)

library(GOplot)
circ <- circle_dat(david, geneFC)
GOCircle(circ)