87 lines
2.3 KiB
R
87 lines
2.3 KiB
R
library(grid)
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library(ComplexHeatmap)
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library(circlize)
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library(RColorBrewer)
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library(dendextend)
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library(dendsort)
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library(gridBase)
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# 加载绘图数据
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data <- read.table(file = 'D:/code/R/1.csv', header = TRUE, row.names = 1, sep = ',')
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# 查看数据
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head(data)
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# 转化matrix格式矩阵及数据归一化
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data <- as.matrix(data)
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cir1 <- t(scale(t(data)))
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# 处理 NA 值
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cir1[is.na(cir1)] <- 0
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# 查看归一化后的数据
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head(cir1)
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# 定义热图颜色梯度
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mycol <- colorRamp2(c(-2.5, 0.3, 3.1), c("blue", "white", "red"))
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mycol1 <- colorRamp2(c(-2, 0, 2), c("#003399", "white", "#cccc00"))
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# 默认参数绘制普通热图
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Heatmap(cir1, row_names_gp = gpar(fontsize = 6),
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column_names_gp = gpar(fontsize = 8),
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col = mycol,
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name = "legend")
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# 计算数据大小范围
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range(cir1)
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# 绘制基础环形热图
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circos.heatmap(cir1, col = mycol)
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circos.clear()
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# 在circos.heatmap()中添加参数进行环形热图的调整和美化
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circos.par(gap.after = c(30))
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circos.heatmap(cir1, col = mycol,
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dend.side = "inside",
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rownames.side = "outside",
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rownames.col = "black",
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rownames.cex = 1.2,
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rownames.font = 1.2,
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bg.border = "black",
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cluster = TRUE)
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circos.clear()
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# 聚类树的调整和美化
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circos.par(gap.after = c(30))
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circos.heatmap(cir1, col = mycol, dend.side = "inside",
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rownames.side = "outside",
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track.height = 0.28,
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rownames.col = "black",
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rownames.cex = 1.3,
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rownames.font = 1.3,
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cluster = TRUE,
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dend.track.height = 0.18,
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dend.callback = function(dend, m, si) {
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color_branches(dend, k = 15, col = 1:15)
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})
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circos.clear()
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# 添加图例标签等
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lg <- Legend(title = "Exp", col_fun = mycol,
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direction = c("vertical"))
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grid.draw(lg)
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# 添加列名
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circos.track(track.index = get.current.track.index(), panel.fun = function(x, y) {
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if (CELL_META$sector.numeric.index == 1) {
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cn <- colnames(cir1)
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n <- length(cn)
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circos.text(rep(CELL_META$cell.xlim[2], n) + convert_x(0.5, "mm"),
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1:n + 5,
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cn, cex = 0.6, adj = c(0, 0.5), facing = "inside")
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}
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}, bg.border = NA)
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circos.clear()
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