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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)
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