1. 例图

image.png

2. 输入数据格式

image.png

3. 代码记录

rm(list = ls())
require(maftools)
options(stringsAsFactors = F) 
library(data.table)

tmp=fread('TCGA-BRCA.mutect2_snv.tsv.gz')
head(tmp) 





library(maftools)
a = read.csv("./maf.txt",sep = '\t',header=F)

dim(a)

head(a,3)

b = read.csv("./maf2.txt",sep = '\t',header=F)

head(b,3)

c= merge.data.frame(a,b ,by.x =c('V1','V2'),by.y =c('V1','V2'))

c$V1 = gsub('-P0','',c$V1)

c$V1 = gsub('-T0','',c$V1)

d = c[!duplicated(c),]

dim(d)

library(dplyr)
d = tidyr::separate(d, col = c('V3.y'), into =c('chr','start'), sep = ":", 
                remove = TRUE)


d = tidyr::separate(d, col = c('V4'), into =c('chr2','stop'), sep = ":", 
                remove = TRUE)

head(d,2)

colnames(tmp)[1:9]

e = d[,c(1,2,4,5,7,8,9,10,3)]

colnames(e) = c( "Tumor_Sample_Barcode", "Hugo_Symbol", 
 "Chromosome", "Start_Position", 
 "End_Position", "Reference_Allele", "Tumor_Seq_Allele2", 
 "HGVSp_Short" , 'Variant_Classification') 

e$Variant_Type = ifelse(
 e$Reference_Allele %in% c('A','C','T','G') & e$Tumor_Seq_Allele2 %in% c('A','C','T','G'),
 'SNP','INDEL'
)

head(e,2)

write.table(e,file = 'e.txt',quote =F,sep ='\t',row.names = F)

tcga.brca = read.maf(maf = e,
 vc_nonSyn=names(tail(sort(table(e$Variant_Classification )))))



oncoplot(maf = tcga.brca,top = 50,writeMatrix = T)

clin <- read.table("cli.txt",header=TRUE)

tcga.brca = read.maf(maf = e, clinicalData = clin,
 vc_nonSyn=names(tail(sort(table(e$Variant_Classification )))))

colnames(clin)

library(ComplexHeatmap)

mut = read.table('./onco_matrix.txt',header =T,sep = '\t',check.names = F)

dim(mut)

"#DC143C","#0000FF","#20B2AA","#FFA500","#9370DB","#98FB98","#F08080"

col <- c( "Multi_Hit" = "#DC143C" , 
         "STOP_GAINED" = "#0000FF",
        "MISSENSE" = '#20B2AA',
         'SPLICE' = '#FFA500',
         'INFRAME_DEL' = '#9370DB',
         'FRAMESHIFT' = '#98FB98', 
         'CNV' = '#F08080'
        )
#指定变异的样子，x,y,w,h代表变异的位置(x,y)和宽度(w)，高度(h)
alter_fun <- list(
  background = function(x, y, w, h) {
    grid.rect(x, y, w-unit(0.5, "mm"), h-unit(0.5, "mm"), 
              gp = gpar(fill = "#CCCCCC", col = NA))
  },
  Multi_Hit = function(x, y, w, h) {
    grid.rect(x, y, w-unit(0.5, "mm"), h-unit(0.5, "mm"), 
              gp = gpar(fill = col["Multi_Hit"], col = NA))
  },
      STOP_GAINED = function(x, y, w, h) {
    grid.rect(x, y, w-unit(0.5, "mm"), h-unit(0.5, "mm"), 
              gp = gpar(fill = col["STOP_GAINED"], col = NA))
  },
      MISSENSE = function(x, y, w, h) {
    grid.rect(x, y, w-unit(0.5, "mm"), h-unit(0.5, "mm"), 
              gp = gpar(fill = col["MISSENSE"], col = NA))
  },
      SPLICE = function(x, y, w, h) {
    grid.rect(x, y, w-unit(0.5, "mm"), h-unit(0.5, "mm"), 
              gp = gpar(fill = col["SPLICE"], col = NA))
  },
      INFRAME_DEL = function(x, y, w, h) {
    grid.rect(x, y, w-unit(0.5, "mm"), h-unit(0.5, "mm"), 
              gp = gpar(fill = col["INFRAME_DEL"], col = NA))
  },
          FRAMESHIFT = function(x, y, w, h) {
    grid.rect(x, y, w-unit(0.5, "mm"), h-unit(0.5, "mm"), 
              gp = gpar(fill = col["FRAMESHIFT"], col = NA))
  },
  CNV = function(x, y, w, h) {
    grid.rect(x, y, w-unit(0.5, "mm"), h*0.33,  
              gp = gpar(fill = col["CNV"], col = NA))
  }
)

heatmap_legend_param <- list(title = "Alternations", 
                             at = c("Multi_Hit" ,  "STOP_GAINED" , "MISSENSE" ,'SPLICE' ,'INFRAME_DEL' ,'FRAMESHIFT', 'CNV'), 
                             labels = c("Multi_Hit" ,  "STOP_GAINED" , "MISSENSE" ,'SPLICE' ,'INFRAME_DEL' ,'FRAMESHIFT', 'CNV'))

column_title <- "This is Oncoplot "  

colnames(clin)

oncoPrint(mut,
          bottom_annotation = ha, #注释信息在底部
          alter_fun = alter_fun, col = col,  
          column_title = column_title, heatmap_legend_param = heatmap_legend_param )

s = clin[order(clin$groups),]
sample_order <- as.character(s$Tumor_Sample_Barcode)

mut1 = mut[,sample_order]

col_os = circlize::colorRamp2(c(0, 4000), c("white", "red"))
ha<-HeatmapAnnotation(groups = s$groups,
                      Age=s$age,
                      Gender=s$sex, 
                      stage = s$stage,
                      
                      #指定颜色
                      col = list(groups = c("MPR" = "orange","NR" = "green","pCR" = "skyblue" ),
                                 #Age = c(">Median" =  "red", "<Median" = "blue"),
                                
                                 os = col_os),
                      show_annotation_name = TRUE,
                      annotation_name_gp = gpar(fontsize = 7))

sample_order

p = oncoplot_anno = oncoPrint(mut1,bottom_annotation = ha,
              alter_fun = alter_fun, col = col, 
              column_order = sample_order,
              remove_empty_columns = TRUE, #去掉空列
              remove_empty_rows = TRUE, #去掉空行
                          show_column_names =T,
              column_title = column_title, heatmap_legend_param = heatmap_legend_param) 
oncoplot_anno





pdf('heatmap.pdf',height = 8,width = 8)
print(p)
dev.off()







ha<-HeatmapAnnotation(Age=clin$age,
                      Gender=clin$sex, 
                      stage = clin$stage,
                      groups = clin$groups,
                      col = list(groups = c('MPR' = '#FF6347','NR' = '#6A5ACD','pCR' = '#8B008B')),  
                      show_annotation_name = TRUE,
                      annotation_name_gp = gpar(fontsize = 7))



sample_order



oncoPrint(mut1,
          bottom_annotation = ha, #注释信息在底部
           remove_empty_columns = TRUE, #去掉空列
            remove_empty_rows = TRUE, #去掉空行
          alter_fun = alter_fun, col = col, column_order = sample_order,
          column_title = column_title, heatmap_legend_param = heatmap_legend_param )