我们今天学习如何利用complexheatmap添加缩放和链接注释，以及如何加入词云图等。
前面我们测试过，热图中有很多行或列，但是我们只想标记其中的一些情况，用的是anno_mark。anno_mark()用于标记行或列的子集并用线连接到标签。anno_mark()至少需要两个参数：at、labels，其中at是原始矩阵的索引和labels相应的文本。
library(ComplexHeatmap)
library(circlize)
library(dendextend)
library(patchwork)
library(wordcloud)
library(simplifyEnrichment)
m = matrix(rnorm(1000), nrow = 100)
rownames(m) = 1:100
ha = rowAnnotation(foo = anno_mark(at = c(1:4, 20, 60, 97:100), labels = month.name[1:10]))
Heatmap(m, name = "mat", cluster_rows = FALSE, right_annotation = ha,
row_names_side = "left", row_nam
但是，anno_mark()将热图上的单行或单列连接到标签，如果我们想多行或者多列链接到标签怎么办？ 注释功能anno_link()将行或列的子集连接到可以添加更全面图形的绘图区域。
set.seed(123)
m = matrix(rnorm(100*10), nrow = 100)
subgroup = sample(letters[1:3], 100, replace = TRUE, prob = c(1, 5, 10))
rg = range(m)
panel_fun = function(index, nm) {
pushViewport(viewport(xscale = rg, yscale = c(0, 2)))
grid.rect()
grid.xaxis(gp = gpar(fontsize = 8))
grid.boxplot(m[index, ], pos = 1, direction = "horizontal")
popViewport()
}
anno = anno_link(align_to = subgroup, which = "row", panel_fun = panel_fun,
size = unit(2, "cm"), gap = unit(1, "cm"), width = unit(4, "cm"))
Heatmap(m, name = "mat", right_annotation = rowAnnotation(foo = anno), row_split = subgroup)
anno_link()的重要参数是：
align_to：它定义了绘图区域（或框）如何对应于热图中的行或列。如果该值是一个索引列表，则每个框对应于列表中一个向量中带有索引的行或列。如果该值是与热图中的行或列具有相同长度的分类变量（例如因子或字符向量），则每个框对应于分类变量中每个级别的行/列。
panel_fun: 自定义函数，定义如何在框中绘制图形。该函数必须有一个index参数，它是框对应的行/列的索引。它可以有第二个参数nm，即热图中所选部分的“名称”。如果将其指定为分类变量或带有名称的列表，则对应的值nm来自align_to。
size: 盒子的大小。它们可以是纯数字，它们被视为热图总高度/宽度的相对分数。size的值也可以是绝对单位。
gap: 盒子之间的间隙。它应该是一个unit对象。
=======词云图======
set.seed(123)
words = sapply(1:30, function(x) strrep(sample(letters, 1), sample(3:10, 1)))
fontsize = runif(30, min = 5, max = 30)
library(grid)
gb = word_cloud_grob(words, fontsize = fontsize, max_width = unit(100, "mm"))
grid.newpage()
grid.draw(gb)
grid.rect(width = grobWidth(gb), height = grobHeight(gb), gp = gpar(fill = NA))
#上面是个最基本的词云图。单词按字体的大小排序，随机分配颜色。这里的max_width参数控制框的“最大宽度”。
#可以通过col来改变颜色
gb = word_cloud_grob(words, fontsize = fontsize, max_width = unit(100, "mm"), col = 1:30)
grid.newpage()
grid.draw(gb)
grid.rect(width = grobWidth(gb), height = grobHeight(gb), gp = gpar(fill = NA))
#可以自己制定任何形式的col
library(circlize)
col_fun = colorRamp2(c(5, 17, 30), c("blue", "black", "red"))
gb = word_cloud_grob(words, fontsize = fontsize, max_width = unit(100, "mm"),
col = col_fun)
grid.newpage()
grid.draw(gb)
grid.rect(width = grobWidth(gb), height = grobHeight(gb), gp = gpar(fill = NA))
=====词云图作为heatmap注释======
gb = word_cloud_grob(words, fontsize = fontsize, max_width = unit(100, "mm"))
gb_h = grobHeight(gb) #获得词云图的高度
gb_w = grobWidth(gb) #获得词云图的宽度
m = matrix(rnorm(100), 10)
ht = Heatmap(m, cluster_rows = FALSE)
ht
panel_fun = function(index, nm) {
grid.rect(gp = gpar(fill = "#EEEEEE", col = NA))
grid.draw(gb)
}
ht + rowAnnotation(word_cloud = anno_link(align_to = 1:3, which = "row",
panel_fun = panel_fun, size = gb_h,
width = gb_w + unit(5, "mm"), # the link is 5mm
link_gp = gpar(fill = "#EEEEEE", col = NA)
))
=========实例测试=========
tmp_file = tempfile()
download.file("https://jokergoo.github.io/word_cloud_annotation_example.RData", destfile = tmp_file, quiet = TRUE)
load(tmp_file)
mat[1:6, 1:6]
#先做一个基本的heatmap
Heatmap(mat, col = colorRamp2(c(0, 1), c("white", "red")),
name = "Similarity",
show_row_names = FALSE, show_column_names = FALSE,
show_row_dend = FALSE, show_column_dend = FALSE,
row_split = cl, column_split = cl,
border = "#404040", row_title = NULL, column_title = NULL,
row_gap = unit(0, "mm"), column_gap = unit(0, "mm"))
ht = Heatmap(mat, col = colorRamp2(c(0, 1), c("white", "red")),
name = "Similarity",
show_row_names = FALSE, show_column_names = FALSE,
show_row_dend = FALSE, show_column_dend = FALSE,
row_split = cl, column_split = cl,
border = "#404040", row_title = NULL, column_title = NULL,
row_gap = unit(0, "mm"), column_gap = unit(0, "mm"))
#首先获得分组信息
align_to = split(seq_len(nrow(mat)), cl)
align_to = align_to[names(align_to) != "0"]
align_to = align_to[names(align_to) %in% names(keywords)]
align_to
#获得每个组的注释信息
fontsize_range = c(4, 16)
gbl = lapply(names(align_to), function(nm) {
kw = keywords[[nm]][, 1]
freq = keywords[[nm]][, 2]
fontsize = scale_fontsize(freq, rg = c(1, max(10, freq)), fs = fontsize_range)
word_cloud_grob(text = kw, fontsize = fontsize)
})
names(gbl) = names(align_to)
gbl
#获得每个组的宽度和高度信息
margin = unit(8, "pt")
gbl_h = lapply(gbl, function(x) convertHeight(grobHeight(x), "cm") + margin)
gbl_h = do.call(unit.c, gbl_h)
gbl_w = lapply(gbl, function(x) convertWidth(grobWidth(x), "cm"))
gbl_w = do.call(unit.c, gbl_w)
gbl_w = max(gbl_w) + margin
panel_fun = function(index, nm) {
# background
grid.rect(gp = gpar(fill = "#DDDDDD", col = NA))
# border
grid.lines(c(0, 1, 1, 0), c(0, 0, 1, 1), gp = gpar(col = "#AAAAAA"),
default.units = "npc")
gb = gbl[[nm]]
# a viewport within the margins
pushViewport(viewport(x = margin/2, y = margin/2,
width = grobWidth(gb), height = grobHeight(gb),
just = c("left", "bottom")))
grid.draw(gb)
popViewport()
}
ht = ht + rowAnnotation(keywords = anno_link(align_to = align_to,
which = "row", panel_fun = panel_fun,
size = gbl_h, gap = unit(2, "mm"),
width = gbl_w + unit(5, "mm"), # 5mm for the link
link_gp = gpar(fill = "#DDDDDD", col = "#AAAAAA"),
internal_line = FALSE)) # you can set it to TRUE to see what happens
draw(ht, ht_gap = unit(2, "pt"))
