将感兴趣的gene list 富集到差异矩阵中

m(list = ls())
options(stringsAsFactors = F)

library(fgsea)
library(org.Hs.eg.db)
library(dplyr)
library(clusterProfiler)
# ISGgenes为ISG基因的list
#读取excel
library(readxl)
ISGgenes<-read_excel("EMT list.xls",sheet = 1)
# 将ISGgenes转换为ENTREZID
s2e<- bitr(ISGgenes$gene, fromType = "SYMBOL",
                 toType="ENTREZID",
                 OrgDb="org.Hs.eg.db")
ISGgenes1 <- inner_join(ISGgenes,s2e,by=c("gene"="SYMBOL"))
# ISGgenes1即为两列，一列是SYMBOL，一列是ENTREZID，其最为比对信号通路存在
write.csv(ISGgenes1,"ISGgenes1.csv",row.names = F)

#处理自己所要看的数据集（包含所有的基因）
HK3_1<-read.csv("mRNAvol.csv",header = T)
HK3_5<- bitr(HK3_1$GeneSymbol, fromType = "SYMBOL",
             toType="ENTREZID",
             OrgDb="org.Hs.eg.db")
HK3_6<-inner_join(HK3_1,HK3_5,by=c("GeneSymbol"="SYMBOL"))
             write.csv(HK3_6,"HK3_6.csv",row.names = F)
             
## 1.而后对所要看HK3_6按照logFC进行排序
geneList1 <- HK3_6$logFC
## 2.命名
names(geneList1) = HK3_6$ENTREZID
## 3.排序很重要
geneList1 = sort(geneList1, decreasing = TRUE)
head(geneList1)
# 
library(stats)
ISG_fgseaRes <- fgsea(pathways = ISGgenes1, 
                      stats    = geneList1,
                      nperm =10000,
                  
                      minSize  = 10,
                      maxSize  = 500)
save(ISGgenes1,geneList1,ISG_fgseaRes,file = "EMT-直接作图.Rdata")



#画图
library(enrichplot)
library(ggplot2)


plotEnrichment(ISGgenes1$ENTREZID,
               geneList1) + labs(title="EMT signaling pathway")+geom_line(color="green",size=2.5)
plotGseaTable(ISGgenes1,geneList1, ISG_fgseaRes, 
              gseaParam=0.3)
dev.off

怎么样把上下调控分开，富集不同的颜色，还没学会，知道的请留言，谢谢。