首先，我們需要知道，熱圖的原理就是根據你的matrix或者data.frame中行列數字大小，映射到一個個獨立的小矩形面中的一種對數據直觀演示的一種方法，只是用顏色深淺對數據大小對大面積數據展開后的展示；類似于條形圖-直方圖-餅圖-boxplot，都是對數據的直觀表示。
獲得熱圖有很多的包，就用這個R自帶的pheatmap包來就可以了，也是很漂亮的呀呀呀呀呀呀。
下面是 pheatmap（)的解釋
例子可以用下面的代碼表示
library(pheatmap)
? # Create test 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 = "")
class(test)
str(test)
# Draw heatmaps
pheatmap(test)
pheatmap(test, kmeans_k = 2)
pheatmap(test, scale = "row", clustering_distance_rows = "correlation")
pheatmap(test,scale = "row")
pheatmap(test,scale="column")
pheatmap(test, color = colorRampPalette(c("navy", "white", "firebrick3"))(50))
###break 調節lengend的區間；col調節顏色；scale調節
bk = unique(c(seq(-8,8, length=100)))
pheatmap(test,breaks = bk,,scale="column")
pheatmap(test,breaks=unique(seq(-2,8,length=100)),color=colorRampPalette(c("navy", "white", "firebrick3"))(100))
pheatmap(test, cluster_row = FALSE)
pheatmap(test, legend = FALSE)
# Show text within cells
pheatmap(test, display_numbers = TRUE)
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")
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,legend_breaks = NA)
pheatmap(test, annotation_col = annotation_col, annotation_row = annotation_row)
pheatmap(test, annotation_col = annotation_col, annotation_row = annotation_row,annotation_legend? = F)
# 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")
table(labels_row)
pheatmap(test, annotation_col = annotation_col, labels_row = labels_row)
# Specifying clustering from distance matrix
drows = dist(test, method = "minkowski")
dcols = dist(t(test), method = "minkowski")
pheatmap(test, clustering_distance_rows = drows, clustering_distance_cols = dcols)
# Modify ordering of the clusters using clustering callback option
callback = function(hc, mat){
? sv = svd(t(mat))$v[,1]
? dend = reorder(as.dendrogram(hc), wts = sv)
? as.hclust(dend)
}
pheatmap(test, clustering_callback = callback)
## Not run:
# Same using dendsort package
library(dendsort)
callback = function(hc, ...){dendsort(hc)}
pheatmap(test, clustering_callback = callback)
完整例子：###例子
###創建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 = "")
###建立annotation數據框
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 = "")
class(test)
str(test)
pheatmap(test,scale = "row",clustering_distance_rows = "euclidean",clustering_distance_cols = "euclidean", clustering_method = "complete",
? ? ? ? cluster_rows = TRUE,cluster_cols = TRUE,cutree_rows = NA, cutree_cols = NA,
? ? ? ? color = colorRampPalette(c("navy", "white", "firebrick3"))(100),
? ? ? ? border_color = "grey60",cellwidth = NA, cellheight = NA,
? ? ? ? legend = TRUE, legend_breaks = NA,legend_labels = NA, breaks = unique(c(seq(-6,6, length=100))),
? ? ? ? annotation_row = annotation_row , annotation_col = annotation_col,annotation = NA, annotation_colors = NA, annotation_legend = TRUE,
? ? ? ? annotation_names_row = TRUE, annotation_names_col = TRUE,
? ? ? ? show_rownames = T, show_colnames = T, main = "Heatmap",
? ? ? ? display_numbers = F, number_format = "%.2f", number_color = "grey30")
