R语言绘制热图——pheatmap

pheatmap简介: Pretty Heatmaps——Implementation of heatmaps that offers more control over dimensions and appearance.

library(pheatmap)
#创建数据集test测试矩阵
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 = "")
# 用pheatmap函数画热图
pheatmap(test)

#默认参数下是对行列均进行聚类（可设置cluster_row = FALSE, cluster_col = FALSE不进行行列的聚类；如果进行聚类了，还可以通过设置treeheight_row=0, treeheight_col=0不显示dendrogram），矩阵没有进行标准化（标准化参数为scale，可选"none", "row", "column"），热图的每个小块之间以灰色隔开（参数border_color，如果不想要border可以设置为NA，当然也可以设置成其它颜色），legend显示在右上方（可设置legend = FALSE不显示legend）；热图的颜色可利用参数color调整；

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

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"1e-4", "1e-3", "1e-2", "1e-1", "1"))#可自己设置图例

#可设置参数display_numbers将数值显示在热图的格子中，可通过number_format设置数值的格式，较常用的有"%.2f"（保留小数点后两位），"%.1e"（科学计数法显示，保留小数点后一位），number_color设置显示内容的颜色：
pheatmap(test, display_numbers = TRUE, number_format = "%.2f", number_color="purple") #"%.2f"表示保留小数点后两位

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# 在热图格子里展示文本
pheatmap(test, display_numbers = TRUE)
pheatmap(test, display_numbers = TRUE, number_format = "\%.1e")
pheatmap(test, display_numbers = matrix(ifelse(test > 5, "*", ""), nrow(test)))#还可以自己设定要显示的内容；

#pheatmap参数设置改变每个格子的大小
pheatmap(test, cellwidth = 15, cellheight = 12, main = "Example heatmap", fontsize = 8, filename = "test.pdf") #main可设置热图的标题，fontsize设置字体大小，filename可直接将热图存出，支持格式png, pdf, tiff, bmp, jpeg，并且可以通过width, height设置图片的大小；

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#pheatmap还可以显示行或列的分组信息，支持多种分组；
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 = "")
pheatmap(test, annotation_col = annotation_col, annotation_row = annotation_row)

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#设定各个分组的颜色
ann_colors = list(Time = c("white", "firebrick"), #连续数值型分组可设置成渐变
CellType = c(CT1 = "#1B9E77", CT2 = "#D95F02"),
GeneClass = c(Path1 = "#7570B3", Path2 = "#E7298A", Path3 = "#66A61E"))
pheatmap(test, annotation_col = annotation_col, annotation_row = annotation_row,
annotation_colors = ann_colors)

#pheatmap还能够根据特定的条件将热图分隔开；
# cutree_rows, cutree_cols：根据行列的聚类数将热图分隔开；
pheatmap(test,cutree_rows=3,cutree_cols=2)

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#还可以自己设定各个分组的颜色
ann_colors = list(Time = c("white", "firebrick"), #连续数值型分组可设置成渐变
CellType = c(CT1 = "#1B9E77", CT2 = "#D95F02"),
GeneClass = c(Path1 = "#7570B3", Path2 = "#E7298A", Path3 = "#66A61E"))
pheatmap(test, annotation_col = annotation_col, annotation_row = annotation_row,
annotation_colors = ann_colors)
#还可以利用gaps_row, gaps_col自己设定要分隔开的位置
pheatmap(test, annotation_col = annotation_col, cluster_rows = FALSE, gaps_row = c(10, 14),
cutree_col = 2)

pheatmap简介: Pretty Heatmaps——Implementation of heatmaps that offers more control over dimensions and appearance.

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library(pheatmap)
#创建数据集test测试矩阵
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 = "")
# 用pheatmap函数画热图
pheatmap(test)

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

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"1e-4", "1e-3", "1e-2", "1e-1", "1"))#可自己设置图例

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# 在热图格子里展示文本
pheatmap(test, display_numbers = TRUE)
pheatmap(test, display_numbers = TRUE, number_format = "\%.1e")
pheatmap(test, display_numbers = matrix(ifelse(test > 5, "*", ""), nrow(test)))#还可以自己设定要显示的内容；

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#pheatmap还可以显示行或列的分组信息，支持多种分组；
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 = "")
pheatmap(test, annotation_col = annotation_col, annotation_row = annotation_row)

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#设定各个分组的颜色
ann_colors = list(Time = c("white", "firebrick"), #连续数值型分组可设置成渐变
CellType = c(CT1 = "#1B9E77", CT2 = "#D95F02"),
GeneClass = c(Path1 = "#7570B3", Path2 = "#E7298A", Path3 = "#66A61E"))
pheatmap(test, annotation_col = annotation_col, annotation_row = annotation_row,
annotation_colors = ann_colors)

#pheatmap还能够根据特定的条件将热图分隔开；
# cutree_rows, cutree_cols：根据行列的聚类数将热图分隔开；
pheatmap(test,cutree_rows=3,cutree_cols=2)

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#还可以自己设定各个分组的颜色
ann_colors = list(Time = c("white", "firebrick"), #连续数值型分组可设置成渐变
CellType = c(CT1 = "#1B9E77", CT2 = "#D95F02"),
GeneClass = c(Path1 = "#7570B3", Path2 = "#E7298A", Path3 = "#66A61E"))
pheatmap(test, annotation_col = annotation_col, annotation_row = annotation_row,
annotation_colors = ann_colors)
#还可以利用gaps_row, gaps_col自己设定要分隔开的位置
pheatmap(test, annotation_col = annotation_col, cluster_rows = FALSE, gaps_row = c(10, 14),
cutree_col = 2)