绘制好看的热图（pheatmap）
pheatmap全称为pretty heamap；
pheatmap(mat, color = colorRampPalette(rev(brewer.pal(n = 7, name =
"RdYlBu")))(100), kmeans_k = NA, breaks = NA, border_color = "grey60",
cellwidth = NA, cellheight = NA, scale = "none", cluster_rows = TRUE,
cluster_cols = TRUE, clustering_distance_rows = "euclidean",
clustering_distance_cols = "euclidean", clustering_method = "complete",
clustering_callback = identity2, cutree_rows = NA, cutree_cols = NA,
treeheight_row = ifelse(cluster_rows, 50, 0),
treeheight_col = ifelse(cluster_cols, 50, 0), legend = TRUE,
legend_breaks = NA, legend_labels = NA, annotation_row = NA,
annotation_col = NA, annotation = NA, annotation_colors = NA,
annotation_legend = TRUE, drop_levels = TRUE, show_rownames = T,
show_colnames = T, main = NA, fontsize = 10, fontsize_row = fontsize,
fontsize_col = fontsize, display_numbers = F, number_format = "%.2f",
number_color = "grey30", fontsize_number = 0.8 * fontsize,
gaps_row = NULL, gaps_col = NULL, labels_row = NULL,
labels_col = NULL, filename = NA, width = NA, height = NA,
silent = FALSE, ...)
参数较多，但是直接用默认参数就能产生比较好看的热图了；下面以例子的形式给出pheatmap的一些重要参数的用法：
#首先构建一个矩阵用于测试：
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 = "")
#test为20行10列的矩阵：
#采取默认参数直接出图
library(pheatmap)
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；
#可自由设置legend的标签
pheatmap(test, cluster_row = FALSE, legend_breaks = -1:4, legend_labels = c("0",
"1e-4", "1e-3", "1e-2", "1e-1", "1"))
#在legend上的-1~4的位置显示"0", "1e-4", "1e-3", "1e-2", "1e-1", "1"
#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
pheatmap(test, display_numbers = TRUE, number_format = "%.1e") #"%.1e"表示以科学计数法表示，保留小数点后一位
#还可以自己设定要显示的内容；
pheatmap(test, display_numbers = matrix(ifelse(test > 5, "*", ""), nrow(test)))
#pheatmap还提供了参数设置每个格子的大小
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；
#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)
#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)
#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)
#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)
#可以设置labels_row, labels_col自己设定行或列的标签
labels_row = c("", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "Il10", "Il15", "Il1b")
pheatmap(test, annotation_col = annotation_col, labels_row = labels_row)
欢迎关注生信人