肿瘤生信科研：绘制突变景观图（mutation landscape）

简说基因

发布于 2024-03-01 17:29:42

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发布于 2024-03-01 17:29:42

文章被收录于专栏：简说基因

肿瘤生信科研经常会画突变的景观图，或者叫瀑布图，用 maftools 包可以实现简单的 Landscape 图，但是当图形比较复杂时，maftools 就不能胜任了，可以用 ComplexHeatmap 包来画。

实际上，Landscape 图是热图的一种：图形由许多方块组成，根据突变类型的不同，方块被渲染成不同的颜色。

本文旨在抛砖引玉，更全面地学习 ComplexHeatmap 画景观图的方法，可以参考官方文档：https://jokergoo.github.io/ComplexHeatmap-reference/book/oncoprint.html

安装

安装稳定版本（建议）：

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

BiocManager::install("ComplexHeatmap")

或者安装开发版本：

library(devtools)
install_github("jokergoo/ComplexHeatmap")

绘图

library(ComplexHeatmap)

加载包自带的数据：

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 "  "            "  "            "  "

原数据行是样本，列是基因，需要进行转置，变成行为基因，列为样本。

数据集中有 3 种变异：HOMDEL、AMP 和 MUT，先定义每种变异在热图中的颜色，再定义一个 alter_fun 函数，用以指明突变的形状，高度等。

col = c("HOMDEL" = "blue", "AMP" = "red", "MUT" = "#008000")

# just for demonstration
alter_fun = list(
    background = alter_graphic("rect", fill = "#CCCCCC"),   
    HOMDEL = alter_graphic("rect", fill = col["HOMDEL"]),
    AMP = alter_graphic("rect", fill = col["AMP"]),
    MUT = alter_graphic("rect", height = 0.33, fill = col["MUT"])
)

现在画景观图。我们将 column_title 和 heatmap_legend_param 保存为变量，因为它们在以下代码块中多次使用。

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)

可以看到，一个基础版的景观图就生成了，横坐标是样本，纵坐标上是基因，并且基因和样本是自动重新排序的（先对基因按突变频率从高到低排序，然后对样本进行排序）。

删除空行和空列

默认情况下，如果样本或基因没有突变，它们仍将保留在热图中，但我们可以将 remove_empty_columns 和 remove_empty_rows 设置为 TRUE 来删除它们：

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)

重新排序行和列

可以通过两个顺序向量：row_order 和 column_order 指定行和列的顺序。

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)

景观图注释

在景观图的顶部和右侧，有显示每个基因或每个样本的不同变异数量的条形图，在景观图的左侧是显示每个基因具有变异的样本百分比的文本注释。

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)

默认情况下，条形图注释显示频率。通过在 anno_oncoprint_barplot() 中设置 show_fraction = TRUE ，可将这些值更改为分数：

oncoPrint(mat,
    alter_fun = alter_fun, col = col, 
    top_annotation = HeatmapAnnotation(
        column_barplot = anno_oncoprint_barplot(show_fraction = TRUE)
    ),
    right_annotation = rowAnnotation(
        row_barplot = anno_oncoprint_barplot(show_fraction = TRUE)
    ),
    remove_empty_columns = TRUE, remove_empty_rows = TRUE,
    column_title = column_title, heatmap_legend_param = heatmap_legend_param)

百分比值和行名称在内部构造为文本注释。可以设置 show_pct 和 show_row_names 来打开或关闭它们。pct_side 和 row_names_side 控制放置它们的边。

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)

景观图的条形图注释本质上是普通注释，可以在 HeatmapAnnotation() 或 rowAnnotation() 中添加更多注释：

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)