R语言绘制差异表达基因热图

以下准备学习绘制热图，根据网络反馈，选择pheatmap包
首先根据包的说明文档训练下，为之后按自己需求实际操作打下基础

#### heatmap plotting 2017-10-19
####pheatmap example
library(pheatmap)
##creat a matrix
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

##Draw heatmap
pheatmap(test)
pheatmap(test, kmeans_k = 2)
pheatmap(test, scale = "column", clustering_distance_rows = "correlation")
pheatmap(test, scale = "row", clustering_distance_rows = "correlation")##Pearson 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)##显示表达值
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")##命名
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)

##代码注释（转载于http://blog.sina.com.cn/s/blog_567b43d00101o546.html）
> library(pheatmap)
> pheatmap(data,fontsize=9, fontsize_row=6) #最简单地直接出图
> pheatmap(data, scale = "row", clustering_distance_row = "correlation", fontsize=9, fontsize_row=6) #改变排序算法
> pheatmap(data, color = colorRampPalette(c("navy", "white", "firebrick3"))(50), fontsize=9, fontsize_row=6) #自定义颜色
> pheatmap(data, cluster_row=FALSE, fontsize=9, fontsize_row=6) #关闭按行排序
> pheatmap(data, legend = FALSE, fontsize=9, fontsize_row=6) #关闭图例
> pheatmap(data, cellwidth = 6, cellheight = 5, fontsize=9, fontsize_row=6) #设定格子的尺寸
> color.map patientcolors hc dd.col groups annotation pheatmap(data, annotation=annotation, fontsize=9, fontsize_row=6) #为样品分组
> Var1 = c("navy", "skyblue")
> Var2 = c("snow", "steelblue")
> names(Var1) = c("class1", "class2")
> ann_colors = list(Var1 = Var1, Var2 = Var2)
> pheatmap(data, annotation=annotation, annotation_colors = ann_colors, fontsize=9, fontsize_row=6) #为分组的样品设定颜色