（转帖）-热图最佳实践-pheatmap-1

原文地址：https://mp.weixin.qq.com/s/P5VcsumN8X6AfydTRY-V6Q

用pheatmap来绘图首先要安装这个包，它就一个功能，画出热图即可，号称是pretty heatmap，的确比其它的好用很多。我以前写过《一步一步学习heatmap.2》的教程，很简单的那种，所以就没有公布在博客上面，结果发现很多其它博客居然能先我一步发出。其实包括本次的pheatmap指南，都没什么好发，的在R里面也是傻瓜式出图，无法就是自己熟练一下参数而已，又不是开发一个包，没什么技术含量。我这里单独提一下pheatmap是因为它的确非常好用，将会是我画热图的不二之选。比如下面这个，是我最喜欢的：

pheatmap

里面该有的信息一应俱全了，包括基因可以分成上下调来显色，基因和样本都可以单独聚类，单独排序，样本也可以具体再分组。热图也可以调整配色方案，单元格的宽度和高度都可以自由调整。把它说明书的代码一句句运行一遍就明白了。

ftp://cran.r-project.org/pub/R/web/packages/pheatmap/pheatmap.pdf

代码如下：

PS：我代码复制到博客就中英文标点被弄混了，请不要直接复制我的点，一行行点敲到R里面

# Create test matrix

## Just replace the test matrix with your own data.

test = matrix(rnorm(200), 20, 10)

test[1:10, seq(1, 10, 2)] = test[1:10, seq(1, 10, 2)] + 3

test[11:20, seq(2, 10, 2)] = test[11:20, seq(2, 10, 2)] + 2

test[15:20, seq(2, 10, 2)] = test[15:20, seq(2, 10, 2)] + 4

colnames(test) = paste("Test", 1:10, sep = "")

rownames(test) = paste("Gene", 1:20, sep = "")

# Draw heatmaps

pheatmap(test)

pheatmap(test, kmeans_k = 2)

pheatmap(test, scale = "row", clustering_distance_rows = "correlation")

pheatmap(test, color = colorRampPalette(c("navy", "white", "firebrick3"))(50) )

pheatmap(test, cluster_row = FALSE)

pheatmap(test, legend = FALSE)

# Show text within cells

pheatmap(test, display_numbers = TRUE)

pheatmap(test, display_numbers = TRUE, number_format = "\%.1e")

pheatmap(test, display_numbers = matrix(ifelse(test > 5, "*", ""), nrow(test)))

pheatmap(test, cluster_row = FALSE, legend_breaks = -1:4, legend_labels = c("0",

"1e-4", "1e-3", "1e-2", "1e-1", "1"))

# Fix cell sizes and save to file with correct size

pheatmap(test, cellwidth = 15, cellheight = 12, main = "Example heatmap")

pheatmap(test, cellwidth = 15, cellheight = 12, fontsize = 8, filename = "test.pdf")

# Generate annotations for rows and columns

annotation_col = data.frame(

CellType = factor(rep(c("CT1", "CT2"), 5)),

Time = 1:5

)

rownames(annotation_col) = paste("Test", 1:10, sep = "")

annotation_row = data.frame(

GeneClass = factor(rep(c("Path1", "Path2", "Path3"), c(10, 4, 6)))

)

rownames(annotation_row) = paste("Gene", 1:20, sep = "")

# Display row and color annotations

pheatmap(test, annotation_col = annotation_col)

pheatmap(test, annotation_col = annotation_col, annotation_legend = FALSE)

pheatmap(test, annotation_col = annotation_col, annotation_row = annotation_row)

# Specify colors

ann_colors = list(

Time = c("white", "firebrick"),

CellType = c(CT1 = "#1B9E77", CT2 = "#D95F02"),

GeneClass = c(Path1 = "#7570B3", Path2 = "#E7298A", Path3 = "#66A61E")

)

pheatmap(test, annotation_col = annotation_col, annotation_colors = ann_colors, main = "Title")

pheatmap(test, annotation_col = annotation_col, annotation_row = annotation_row,

annotation_colors = ann_colors)

pheatmap(test, annotation_col = annotation_col, annotation_colors = ann_colors[2])

# Gaps in heatmaps

pheatmap(test, annotation_col = annotation_col, cluster_rows = FALSE, gaps_row = c(10, 14))

pheatmap(test, annotation_col = annotation_col, cluster_rows = FALSE, gaps_row = c(10, 14),

cutree_col = 2)

# Show custom strings as row/col names

labels_row = c("", "", "", "", "", "", "", "", "", "", "", "", "", "", "",

"", "", "Il10", "Il15", "Il1b")

pheatmap(test, annotation_col = annotation_col, labels_row = labels_row)

# Specifying clustering from distance matrix

drows = dist(test, method = "minkowski")

dcols = dist(t(test), method = "minkowski")

pheatmap(test, clustering_distance_rows = drows, clustering_distance_cols = dcols)

# Modify ordering of the clusters using clustering callback option

callback = function(hc, mat){

sv = svd(t(mat))$v[,1]

dend = reorder(as.dendrogram(hc), wts = sv)

as.hclust(dend)

}

pheatmap(test, clustering_callback = callback)

## Not run:

# Same using dendsort package

library(dendsort)

callback = function(hc, ...){dendsort(hc)}

pheatmap(test, clustering_callback = callback)

## End(Not run)