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超详细的R语言热图之complexheatmap系列6
我们继续学习complexheatmap包的内容，这是本系列的第6篇文章。本系列内容非常多，将通过多篇推文逐渐介绍，欢迎大家关注我的公众号：医学和生信笔记。
本篇内容主要介绍热图中图例的各种设置！
complexheatmap系列第1篇：超详细的R语言热图之complexheatmap系列1
complexheatmap系列第2篇：超详细的R语言热图之complexheatmap系列2
complexheatmap系列第3篇：超详细的R语言热图之complexheatmap系列3
complexheatmap系列第4篇：超详细的R语言热图之complexheatmap系列4
complexheatmap系列第5篇：超详细的R语言热图之complexheatmap系列5
第五章 图例
简单图例会自动绘出，复杂图例需要手动修改。所有的图例都可以通过Legend()函数画出，都属于Legend类。热图主体的图例可以通过heatmap_legend_param参数(Heatmap()中)调整，注释条的图例可以通过annatation_legend_param参数(HeatmapAnnotation()中)调整。
5.1 连续性变量的图例
library(ComplexHeatmap)
## 载入需要的程辑包：grid
## ========================================
## ComplexHeatmap version 2.8.0
## Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
## Github page: https://github.com/jokergoo/ComplexHeatmap
## Documentation: http://jokergoo.github.io/ComplexHeatmap-reference
##
## If you use it in published research, please cite:
## Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional
## genomic data. Bioinformatics 2016.
##
## The new InteractiveComplexHeatmap package can directly export static
## complex heatmaps into an interactive Shiny app with zero effort. Have a try!
##
## This message can be suppressed by:
## suppressPackageStartupMessages(library(ComplexHeatmap))
## ========================================
library(circlize)
## ========================================
## circlize version 0.4.13
## CRAN page: https://cran.r-project.org/package=circlize
## Github page: https://github.com/jokergoo/circlize
## Documentation: https://jokergoo.github.io/circlize_book/book/
##
## If you use it in published research, please cite:
## Gu, Z. circlize implements and enhances circular visualization
## in R. Bioinformatics 2014.
##
## This message can be suppressed by:
## suppressPackageStartupMessages(library(circlize))
## ========================================
col_fun = colorRamp2(c(0, 0.5, 1), c("blue", "white", "red"))
lgd = Legend(col_fun = col_fun, title = "foo")
draw(lgd)
简单图例会自动绘出：
Heatmap(matrix(rnorm(100),10),
top_annotation = HeatmapAnnotation(foo = 1:10)
)
当然也可以使用参数手动指定，改变样式等：
Heatmap(matrix(rnorm(100), 10),
heatmap_legend_param = list(
title = "rnorm", at = c(-2, 0, 2),
labels = c("neg_two", "zero", "pos_two")
),
top_annotation = HeatmapAnnotation(
foo = 1:10,
annotation_legend_param = list(foo = list(title = "foo_top_anno"))
))
可以自由设置图例刻度位置、标签、图例标题、高度、宽度、标签颜色、字体等：
lgd <- Legend(col_fun = col_fun, title = "foo1", at = c(0,0.25,0.5,0.75,1))
draw(lgd)
lgd <- Legend(col_fun = col_fun, title = "foo2", at = c(0,0.25,0.5,0.75,1),
labels = c("hi","ha","hei","hoo","hey"))
draw(lgd)
legd <- Legend(col_fun = col_fun, title = "foo3", legend_height = unit(8, "cm"))
draw(legd)
lgd <- Legend(col_fun = col_fun, title = "foo1", grid_width = unit(3, "cm")) # 竖直型的图例用`grid_width`
draw(lgd)
修改图例标签样式：
lgd <- Legend(col_fun = col_fun, title = "foo", legend_gp = gpar(col = "red", font = 5))
draw(lgd)
修改图例边框颜色：
lgd <- Legend(col_fun = col_fun, title = "foo", border = "red")
draw(lgd)
修改图例标题位置：
lgd <- Legend(col_fun = col_fun, title = "foooooooo", title_position = "leftcenter-rot",
legend_height = unit(4, "cm"))
draw(lgd)
使用特殊字体，公式等：
lgd <- Legend(col_fun = col_fun, title = expression(hat(beta) == (X^t * X)^{-1} * X^t * y),
at = c(0, 0.25, 0.5, 0.75, 1), labels = expression(alpha, beta, gamma, delta, epsilon))
draw(lgd)
旋转图例标签：
lgd <- Legend(col_fun = col_fun, name = "foo1", labels_rot = 90)
draw(lgd)
标签拥挤会自动调整：
lgd <- Legend(col_fun = col_fun, title = "foo", at = c(0, 0.1, 0.15, 0.5, 0.9, 0.95, 1))
draw(lgd)
水平排列的图例，只需要一个参数:direction="horizontal"除了图例宽度使用legend_width外，其余调整和竖直型完全一样，就不在详细介绍了。
lgd <- Legend(col_fun = col_fun, title = "foooooooo", direction = "horizontal",
title_position = "lefttop")
draw(lgd)
5.2 离散型变量的图例
基本上和连续性图例一模一样，就不多说了~~
lgd <- Legend(at = 1:6, title = "foo", legend_gp = gpar(fill = 1:6))
draw(lgd)
lgd <- Legend(labels = month.name[1:6], title = "foo", legend_gp = gpar(fill = 1:6))
draw(lgd)
离散图例展示连续性颜色映射：
at <- seq(0, 1, by = 0.2)
lgd <- Legend(at = at, title = "foo", legend_gp = gpar(fill = col_fun(at)))
draw(lgd)
离散型图例比连续型图例多了一个变成多列/多行的功能：
lgd <- Legend(labels = month.name[1:10], legend_gp = gpar(fill = 1:10),
title = "foo", ncol = 3)
draw(lgd)
还可以改变图例形状，配合type和pch参数：
lgd <- Legend(labels = month.name[1:6], title = "foo", type = "points",
pch = 1:6, legend_gp = gpar(col = 1:6), background = "#FF8080")
draw(lgd)
lgd <- Legend(labels = month.name[1:6], title = "foo", type = "points",
pch = letters[1:6], legend_gp = gpar(col = 1:6), background = "white")
draw(lgd)
lgd <- Legend(labels = month.name[1:6], title = "foo", type = "lines",
legend_gp = gpar(col = 1:6, lty = 1:6), grid_width = unit(1, "cm"))
draw(lgd)
lgd <- Legend(labels = month.name[1:6], title = "foo", type = "boxplot",
legend_gp = gpar(fill = 1:6))
draw(lgd)
lgd <- Legend(labels = paste0("pch = ", 26:28), type = "points", pch = 26:28)
draw(lgd)
5.3 多个图例
使用packLegend()排列多个图例，默认会绘制好图例，如果需要手动修改需要用到。
lgd1 <- Legend(at = 1:6, legend_gp = gpar(fill = 1:6), title = "legend1")
lgd2 <- Legend(col_fun = col_fun, title = "legend2", at = c(0, 0.25, 0.5, 0.75, 1))
lgd3 <- Legend(labels = month.name[1:3], legend_gp = gpar(fill = 7:9), title = "legend3")
pd <- packLegend(lgd1, lgd2, lgd3)
# 和下面相同
pd <- packLegend(list = list(lgd1, lgd2, lgd3))
draw(pd)
变成多列/多行，改变行间距/列间距等：
lgd1 <- Legend(at = 1:6, legend_gp = gpar(fill = 1:6), title = "legend1",
nr = 1)
lgd2 <- Legend(col_fun = col_fun, title = "legend2", at = c(0, 0.25, 0.5, 0.75, 1),
direction = "horizontal")
pd <- packLegend(lgd1, lgd2, lgd3, lgd1, lgd2, lgd3, max_width = unit(10, "cm"),
direction = "horizontal", column_gap = unit(5, "mm"), row_gap = unit(1, "cm"))
draw(pd)
5.4 热图主体和注释条的图例
主要是heatmap_legend_param和annotation_legend_param
m <- matrix(rnorm(100), 10)
Heatmap(m, name = "mat", heatmap_legend_param = list(
at = c(-2, 0, 2),
labels = c("low", "zero", "high"),
title = "Some values",
legend_height = unit(4, "cm"),
title_position = "lefttop-rot"
))
ha <- HeatmapAnnotation(foo = runif(10), bar = sample(c("f", "m"), 10, replace = TRUE),
annotation_legend_param = list(
foo = list(
title = "Fooooooh",
at = c(0, 0.5, 1),
labels = c("zero", "median", "one")
),
bar = list(
title = "Baaaaaaar",
at = c("f", "m"),
labels = c("Female", "Male")
)
))
Heatmap(m, name = "mat", top_annotation = ha)
5.5 添加自定义图例
熟悉几个常用函数及参数后，剩下的就是各种排列组合，可以尽情发挥你的想象力。
ha1 = HeatmapAnnotation(pt = anno_points(1:10, gp = gpar(col = rep(2:3, each = 5)),
height = unit(2, "cm")), show_annotation_name = FALSE)
ha2 = HeatmapAnnotation(ln = anno_lines(cbind(1:10, 10:1), gp = gpar(col = 4:5, lty = 1:2),
height = unit(2, "cm")), show_annotation_name = FALSE)
m = matrix(rnorm(100), 10)
ht_list = Heatmap(m, name = "mat1", top_annotation = ha1) +
Heatmap(m, name = "mat2", top_annotation = ha2) +
Heatmap(m[, 1], name = "mat3",
top_annotation = HeatmapAnnotation(
summary = anno_summary(gp = gpar(fill = 2:3))
), width = unit(1, "cm"))
draw(ht_list, ht_gap = unit(7, "mm"), row_km = 2)
lgd_list = list(
Legend(labels = c("red", "green"), title = "pt", type = "points", pch = 16,
legend_gp = gpar(col = 2:3)),
Legend(labels = c("darkblue", "lightblue"), title = "ln", type = "lines",
legend_gp = gpar(col = 4:5, lty = 1:2)),
Legend(labels = c("group1", "group2"), title = "km", type = "boxplot",
legend_gp = gpar(fill = 2:3))
)
draw(ht_list, ht_gap = unit(7, "mm"), row_km = 2, annotation_legend_list = lgd_list)
5.6 图例位置
一个参数的事情
ha1 = HeatmapAnnotation(foo1 = runif(10), bar1 = sample(c("f", "m"), 10, replace = TRUE),
annotation_legend_param = list(
foo1 = list(direction = "horizontal"),
bar1 = list(nrow = 1)))
ha2 = HeatmapAnnotation(foo2 = runif(10), bar2 = sample(c("f", "m"), 10, replace = TRUE),
annotation_legend_param = list(
foo2 = list(direction = "horizontal"),
bar2 = list(nrow = 1)))
ht_list = Heatmap(m, name = "mat1", top_annotation = ha1,
heatmap_legend_param = list(direction = "horizontal")) +
rowAnnotation(sth = runif(10),
annotation_legend_param = list(sth = list(direction = "horizontal"))) +
Heatmap(m, name = "mat2", top_annotation = ha2,
heatmap_legend_param = list(direction = "horizontal"))
draw(ht_list, merge_legend = TRUE, heatmap_legend_side = "bottom",
annotation_legend_side = "bottom")
第六章 热图装饰
热图的每个组成部分都可以在画完之后继续修改，可以通过list_components()函数获取每个组成部分的名字，下面是作者给的例子。
set.seed(123)
mat = matrix(rnorm(80, 2), 8, 10)
mat = rbind(mat, matrix(rnorm(40, -2), 4, 10))
rownames(mat) = paste0("R", 1:12)
colnames(mat) = paste0("C", 1:10)
ha_column1 = HeatmapAnnotation(points = anno_points(rnorm(10)),
annotation_name_side = "left")
ht1 = Heatmap(mat, name = "ht1", km = 2, column_title = "Heatmap 1",
top_annotation = ha_column1, row_names_side = "left")
ha_column2 = HeatmapAnnotation(type = c(rep("a", 5), rep("b", 5)),
col = list(type = c("a" = "red", "b" = "blue")))
ht2 = Heatmap(mat, name = "ht2", row_title = "Heatmap 2", column_title = "Heatmap 2",
bottom_annotation = ha_column2, column_km = 2)
ht_list = ht1 + ht2 +
rowAnnotation(bar = anno_barplot(rowMeans(mat), width = unit(2, "cm")))
draw(ht_list, row_title = "Heatmap list", column_title = "Heatmap list")
list_components()
## [1] "ROOT" "global"
## [3] "global_layout" "global-heatmaplist"
## [5] "main_heatmap_list" "heatmap_ht1"
## [7] "ht1_heatmap_body_wrap" "ht1_heatmap_body_1_1"
## [9] "ht1_heatmap_body_2_1" "ht1_column_title_1"
## [11] "ht1_row_title_1" "ht1_row_title_2"
## [13] "ht1_dend_row_1" "ht1_dend_row_2"
## [15] "ht1_dend_column_1" "ht1_row_names_1"
## [17] "ht1_row_names_2" "ht1_column_names_1"
## [19] "annotation_points_1" "heatmap_ht2"
## [21] "ht2_heatmap_body_wrap" "ht2_heatmap_body_1_1"
## [23] "ht2_heatmap_body_1_2" "ht2_heatmap_body_2_1"
## [25] "ht2_heatmap_body_2_2" "ht2_column_title_1"
## [27] "ht2_dend_column_1" "ht2_dend_column_2"
## [29] "ht2_column_names_1" "ht2_column_names_2"
## [31] "annotation_type_1" "annotation_type_2"
## [33] "heatmap_heatmap_annotation_11" "annotation_bar_1"
## [35] "annotation_bar_2" "global-column_title_top"
## [37] "global_column_title" "global-row_title_left"
## [39] "global_row_title" "global-heatmap_legend_right"
## [41] "heatmap_legend" "global-annotation_legend_right"
## [43] "annotation_legend"
为了防止你记不住，作者提供了风格一致的名字：
decorate_heatmap_body()decorate_annotation()decorate_dend()decorate_title()decorate_dimnames()decorate_row_names(), identical todecorate_dimnames(..., which = "row").decorate_column_names(), identical todecorate_dimnames(..., which = "column").decorate_row_dend(), identical todecorate_dend(..., which = "row").decorate_column_dend(), identical todecorate_dend(..., which = "column").decorate_row_title(), identical todecorate_title(..., which = "row").decorate_column_title(), identical todecorate_title(..., which = "column")
一个例子：
ht_list = draw(ht_list, row_title = "Heatmap list", column_title = "Heatmap list",
heatmap_legend_side = "right", annotation_legend_side = "left")
decorate_heatmap_body("ht1", {
grid.text("outlier", 1.5/10, 2.5/4, default.units = "npc")
grid.lines(c(0.5, 0.5), c(0, 1), gp = gpar(lty = 2, lwd = 2))
}, slice = 2)
decorate_column_dend("ht1", {
tree = column_dend(ht_list)$ht1[[1]]
ind = cutree(as.hclust(tree), k = 2)[order.dendrogram(tree)]
first_index = function(l) which(l)[1]
last_index = function(l) { x = which(l); x[length(x)] }
x1 = c(first_index(ind == 1), first_index(ind == 2)) - 1
x2 = c(last_index(ind == 1), last_index(ind == 2))
grid.rect(x = x1/length(ind), width = (x2 - x1)/length(ind), just = "left",
default.units = "npc", gp = gpar(fill = c("#FF000040", "#00FF0040"), col = NA))
})
decorate_row_names("ht1", {
grid.rect(gp = gpar(fill = "#FF000040"))
}, slice = 2)
decorate_row_title("ht1", {
grid.rect(gp = gpar(fill = "#00FF0040"))
}, slice = 1)
decorate_annotation("points", {
grid.lines(c(0, 1), unit(c(0, 0), "native"), gp = gpar(col = "red"))
})
作者还提供了其他一些例子，就不一一介绍了
sessionInfo()
## R version 4.1.0 (2021-05-18)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 19044)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=Chinese (Simplified)_China.936
## [2] LC_CTYPE=Chinese (Simplified)_China.936
## [3] LC_MONETARY=Chinese (Simplified)_China.936
## [4] LC_NUMERIC=C
## [5] LC_TIME=Chinese (Simplified)_China.936
##
## attached base packages:
## [1] grid stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] circlize_0.4.13 ComplexHeatmap_2.8.0
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.7 cluster_2.1.2 knitr_1.33
## [4] magrittr_2.0.1 BiocGenerics_0.38.0 IRanges_2.26.0
## [7] doParallel_1.0.16 clue_0.3-59 colorspace_2.0-2
## [10] rjson_0.2.20 foreach_1.5.1 highr_0.9
## [13] stringr_1.4.0 tools_4.1.0 parallel_4.1.0
## [16] xfun_0.25 png_0.1-7 iterators_1.0.13
## [19] matrixStats_0.60.0 digest_0.6.27 crayon_1.4.1
## [22] RColorBrewer_1.1-2 S4Vectors_0.30.0 GlobalOptions_0.1.2
## [25] codetools_0.2-18 shape_1.4.6 evaluate_0.14
## [28] stringi_1.7.3 compiler_4.1.0 magick_2.7.3
## [31] stats4_4.1.0 Cairo_1.5-12.2 GetoptLong_1.0.5
以上就是今天的内容，希望大家都能学会！
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超详细的R语言热图之complexheatmap系列2