安装最新版maftools

依照maftools官网（http://www.bioconductor.org/packages/release/bioc/html/maftools.html）说明安装最新版的maftools，旧版的maftools是不包含今天要用的coBarplot的

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("maftools")

试了好多次（linux上不同的R版本及Windows的的R）都没能成功
还有一种办法，就是先下载package后再安装，Linux版：http://www.bioconductor.org/packages/release/bioc/src/contrib/maftools_2.4.05.tar.gz；windows版：http://www.bioconductor.org/packages/release/bioc/bin/windows/contrib/4.0/maftools_2.4.05.zip
以Linux为例，安装package

install.packages("/*/maftools_2.4.05.tar.gz")

准备待比较的两个组的maf文件

library("maftools")
annovarToMaf("Candidate.anno.hg19_multianno.txt.top_gene",  Center = NULL,  refBuild = "hg19",  tsbCol = 'Tumor_Sample_Barcode',  table = "refGene",  basename = "Candidate",  sep = "\t",  MAFobj = FALSE,  sampleAnno = NULL)
annovarToMaf("know.anno.hg19_multianno.txt.top_gene",  Center = NULL,  refBuild = "hg19",  tsbCol = 'Tumor_Sample_Barcode',  table = "refGene",  basename = "know",  sep = "\t",  MAFobj = FALSE,  sampleAnno = NULL)
genecast=read.maf(maf ="Candidate.maf",useAll=TRUE)
know=read.maf(maf ="know.maf",useAll=TRUE)

两个maf文件进行比较

genecast.vs.know <- mafCompare(m1 = genecast, m2 = know, m1Name = 'genecast', m2Name = 'know', minMut = 2, useCNV =FALSE)
write.table(genecast.vs.know$results, file="genecast.vs.know.maf.diff.txt", quote=FALSE, row.names=T,sep="\t")

结果示例

image.png

绘制森林图

pdf("genecast.vs.know.diff.forestplot.pdf",width=6,height=5)
forestPlot(mafCompareRes = genecast.vs.know, pVal = 0.1, color = c('royalblue', 'maroon'), geneFontSize = 0.8)
dev.off()

结果示例

image.png

绘制比较图

r1<-genecast.vs.know$results
g0<-r1[which(r1$pval<0.05),Hugo_Symbol]
g1<-r1[1:5,Hugo_Symbol]
l<-length(g0)
ifelse(l>5,g<-g0,g<-g1)
pdf("genecast.vs.know.maf.diff.coOncoplot.pdf",width=100,height=6)
coOncoplot(m1 = genecast, m2 = know, m1Name = 'genecast', m2Name = 'know', genes = g, removeNonMutated = TRUE)
dev.off()

结果示例

image.png

绘制柱状图

pdf("genecast.vs.know.maf.diff.coBarplot.pdf",width=5.5,height=5.5)
coBarplot(m1 = genecast, m2 = know, m1Name = 'genecast', m2Name = 'know')
dev.off()

结果示例

image.png