相关性热图、差异基因热图等
画热图的包：pheatmap包
pheatmap()函数：
usage：基因和样本都可以单独聚类，排序，聚类再分组，行列注释，配色调整，调整聚类线以及单元格的宽度和高度均可实现
pheatmap()
#构建测试数据
set.seed(1234)
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 = "")
head(test[,1:6])
#加载包：
library(pheatmap)
pheatmap(mat = test)
参数：
- 基本参数：
mat：要输入的矩阵（只能是matrix）
scale："row"对行进行归一化、"column"对列进行归一化
main:热图的标题
pheatmap(mat = test,scale = "column")
pheatmap(mat = test,scale = "row") # 默认
pheatmap(mat = test,scale = "none")
- 控制cell的大小：cellwidth、cellheight（分别设置小格子的行列的宽度）
fontsize（用于控制行列的名字的大小）
fontsize_row、fontsize_col
pheatmap(test, cellwidth = 15, cellheight = 12, fontsize = 10)
pheatmap(test, cellwidth = 15, cellheight = 12, fontsize = 5)
- 控制text：display_numbers = TRUE，参数设定在每个热图格子中显示相应的数字
number_color参数设置数值字体的颜色
number_format：设置数字的显示格式：例如"%.1e"
pheatmap(test, display_numbers = TRUE,number_color = "blue")
pheatmap(test, display_numbers = TRUE, number_format = "%.1e")
pheatmap(test, display_numbers = matrix(ifelse(test > 5, "*", ""), nrow(test))) #指定显示数字的格子
- 行或者列的label: 默认值为输入矩阵的行列名
angle_col：控制行列标签的角度，0, 45, 90, 270 and 315
show_rownames、show_colnames：逻辑值，是否显示行列名
labels_row = c("", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "Il10", "Il15", "Il1b")
pheatmap(test, labels_row = labels_row)
pheatmap(test, labels_row = labels_row,show_colnames = F)
- 设置legend：legend：表示是否设置图例
legend_labels：设置图例的标签
legend_breaks：设定图例显示范围
pheatmap(test, cluster_row = FALSE, legend_breaks = -2:6)
pheatmap(test, cluster_row = FALSE, legend_breaks = -1:4,legend_labels = c("0", "1e-4", "1e-3", "1e-2", "1e-1", "1"))
- 关于聚类的参数：一般都弄成默认
clustering_method：设定不同聚类方法，默认为"complete",可以设定为'ward', 'ward.D', 'ward.D2', 'single', 'complete', 'average', 'mcquitty', 'median' or 'centroid'
cluster_row ,cluster_col：行、列是否聚类，\默认为TRUE
treeheight_row和treeheight_col：设定行和列聚类树的高度，默认为50
clustering_distance_rows = "euclidean",
clustering_distance_cols = "euclidean",
clustering_callback = identity2
cutree_rows, cutree_cols：表示把如图按照行、列分为xx个部分
treeheight_row = ifelse((class(cluster_rows) == "hclust") || cluster_rows,50, 0),
treeheight_col = ifelse((class(cluster_cols) == "hclust") || cluster_cols, 50, 0) - 设定color：
- 设定行、列 annotation：
annotation_row：注释行的数据框，必须和输入的矩阵的行名相同
annotation_col：一个数据框，数据的列名必须和输入
annotation_legend :设置注释信息的图例，逻辑值，表示是否显示注释的图例
# 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 = "")
#用于列注释的数据框的行名必须等于用于作图的矩阵的列名
annotation_row = data.frame(GeneClass = factor(rep(c("Path1", "Path2", "Path3"), c(10, 4, 6))))
rownames(annotation_row) = paste("Gene", 1:20, sep = "")
#用于行注释的数据框的行名必须等于用于作图的矩阵的行名
# 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)
# Change angle of text in the columns
pheatmap(test, annotation_col = annotation_col, annotation_row = annotation_row, angle_col = "45")
pheatmap(test, annotation_col = annotation_col, angle_col = "0")
# 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_row、gaps_col：只有在没有进行聚类时才可以使用gap,其传入的值为一个向量
pheatmap(test, annotation_col = annotation_col, cluster_rows = FALSE, gaps_row = c(10, 14))
pheatmap(test, annotation_col = annotation_col, cluster_cols = FALSE, gaps_col = c(2,5))