ComplexHeatmap绘制全基因组突变景观图

2016/11/07来源：作图丫1 5,353

ComplexHeatmap R包是Zuguang Gu编写的，也是现在文章中利用的较多的R包。这个包能实现的功能很强大，今天给大家介绍一下利用ComplexHeatmap R包中的oncoprint绘制突变景观图。

一、文件格式

1、突变矩阵文件

2、排序文件

二、代码和绘图释义

首先需要安装：打开网址http://www.bioconductor.org/packages/release/bioc/html/ComplexHeatmap.html，找到安装命令：

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

也可以将此R包下载下来进行本地安装。

安装成功后，输入加载命令

library(ComplexHeatmap)
library(circlize)

mat = read.table(system.file("extdata", package = "ComplexHeatmap", 
    "tcga_lung_adenocarcinoma_provisional_ras_raf_mek_jnk_signalling.txt"), 
    header = TRUE, stringsAsFactors = FALSE, sep = "\t")
mat[is.na(mat)] = ""rownames(mat) = mat[, 1]
mat = mat[, -1]
mat=  mat[, -ncol(mat)]
mat = t(as.matrix(mat))
mat[1:3, 1:3]
##      TCGA-05-4384-01 TCGA-05-4390-01 TCGA-05-4425-01
## KRAS "  "            "MUT;"          "  "           
## HRAS "  "            "  "            "  "           
## BRAF "  "            "  "            "  "

mat文件中含有: HOMDEL, AMP and MUT类型突变. 对突变进行颜色和突变分类定义

col = c("HOMDEL" = "blue", "AMP" = "red", "MUT" = "#008000")
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))
    },
    # big blue
    HOMDEL = function(x, y, w, h) {
        grid.rect(x, y, w-unit(0.5, "mm"), h-unit(0.5, "mm"), 
            gp = gpar(fill = col["HOMDEL"], col = NA))
    },
    # bug red
    AMP = function(x, y, w, h) {
        grid.rect(x, y, w-unit(0.5, "mm"), h-unit(0.5, "mm"), 
            gp = gpar(fill = col["AMP"], col = NA))
    },
    # small green
    MUT = function(x, y, w, h) {
        grid.rect(x, y, w-unit(0.5, "mm"), h*0.33, 
            gp = gpar(fill = col["MUT"], col = NA))
    }
)

column_title 和 heatmap_legend_param定义

column_title = "OncoPrint for TCGA Lung Adenocarcinoma, genes in Ras Raf MEK JNK signalling"
heatmap_legend_param = list(title = "Alternations", at = c("HOMDEL", "AMP", "MUT"), 
        labels = c("Deep deletion", "Amplification", "Mutation"))oncoPrint(mat,
    alter_fun = alter_fun, col = col, 
column_title = column_title, heatmap_legend_param = heatmap_legend_param)

删除空行和空列

remove_empty_columns = TRUE 和 remove_empty_rows = TRUE

oncoPrint(mat,
    alter_fun = alter_fun, col = col, 
    remove_empty_columns = TRUE, remove_empty_rows = TRUE,
    column_title = column_title, heatmap_legend_param = heatmap_legend_param)

行和进行排序

row_order = 1:nrow(mat), column_order = sample_order

sample_order = scan(paste0(system.file("extdata", package = "ComplexHeatmap"), 
    "/sample_order.txt"), what = "character")oncoPrint(mat,
    alter_fun = alter_fun, col = col, 
    row_order = 1:nrow(mat), column_order = sample_order,
    remove_empty_columns = TRUE, remove_empty_rows = TRUE,
    column_title = column_title, heatmap_legend_param = heatmap_legend_param)

行和列注释anno_oncoprint_barplot()可以对突变类型进行筛选绘制Bar图。

oncoPrint(mat,
    alter_fun = alter_fun, col = col, 
    top_annotation = HeatmapAnnotation(
        column_barplot = anno_oncoprint_barplot("MUT", border = TRUE, # only MUT
            height = unit(4, "cm"))),
    right_annotation = rowAnnotation(
        row_barplot = anno_oncoprint_barplot(c("AMP", "HOMDEL"),  # only AMP and HOMDEL
            border = TRUE, height = unit(4, "cm"), 
            axis_param = list(side = "bottom", labels_rot = 90))),
    remove_empty_columns = TRUE, remove_empty_rows = TRUE,
    column_title = column_title, heatmap_legend_param = heatmap_legend_param)

对行显示位置进行调整pct_side = "right", row_names_side = "left"

oncoPrint(mat,
    alter_fun = alter_fun, col = col, 
    remove_empty_columns = TRUE, remove_empty_rows = TRUE,
    pct_side = "right", row_names_side = "left",
    column_title = column_title, heatmap_legend_param = heatmap_legend_param)

增加样品分组注释

oncoPrint(mat,
    alter_fun = alter_fun, col = col, 
    remove_empty_columns = TRUE, remove_empty_rows = TRUE,
    top_annotation = HeatmapAnnotation(cbar = anno_oncoprint_barplot(),
        foo1 = 1:172,
        bar1 = anno_points(1:172)),
    left_annotation = rowAnnotation(foo2 = 1:26),
    right_annotation = rowAnnotation(bar2 = anno_barplot(1:26)),
    column_title = column_title, heatmap_legend_param = heatmap_legend_param)

绘制一张带有分组注释的突变景观图就完成了，同时还能对此图增加聚类热图来显示更多信息。

最后自己用测试数据进行绘图，绘制如下：

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