ixxmu
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3 months ago 还没见过ComplexHeatmap版本的单细胞数据Dotplot图？大海哥手把手教你绘制！ by 生信滩
library(Seurat) # DotPlot()library(tidyverse) # 数据整理library(ComplexHeatmap) # 绘制气泡热图library(circlize) # circlize::colorRamp2()library(scRNAtoolVis) # 为了使用pbmc数据集然后我们加载pbmc数据集httest <- system.file("extdata", "htdata.RDS", package = "scRNAtoolVis")pbmc <- readRDS(httest)# add groupspbmc$groups <- rep(c('stim','control'),each = 1319)# add celltypepbmc$celltype <- Seurat::Idents(pbmc)# load markergenedata("top3pbmc.markers")# checkhead(top3pbmc.markers,3)
p <- DotPlot(object = pbmc, features = top3pbmc.markers$gene)p
#提取数据df<- p$dataexp_mat <- df %>%dplyr::select(-pct.exp, -avg.exp) %>%pivot_wider(names_from = id, values_from = avg.exp.scaled) %>%as.data.frame()row.names(exp_mat) <- exp_mat$features.plotexp_mat <- exp_mat[,-1] %>% as.matrix()head(exp_mat)
#数据2percent_mat <- df %>%dplyr::select(-avg.exp, -avg.exp.scaled) %>%pivot_wider(names_from = id, values_from = pct.exp) %>%as.data.frame()row.names(percent_mat) <- percent_mat$features.plotpercent_mat <- percent_mat[,-1] %>% as.matrix()head(percent_mat)
#调色板library(RColorBrewer)quantile(exp_mat, c(0.1, 0.5, 0.9, 0.99))col_fun = circlize::colorRamp2(c(-0.6, 0, 2), brewer.pal(11, "PiYG")[c(11,8,1)])cell_fun = function(j, i, x, y, w, h, fill){grid.rect(x = x, y = y, width = w, height = h,gp = gpar(col = NA, fill = NA))grid.circle(x=x,y=y,r= percent_mat[i, j]/100 * min(unit.c(w, h)),gp = gpar(fill = col_fun(exp_mat[i, j]), col = NA))}
Heatmap(exp_mat,name = "hp",heatmap_legend_param = list(title = "expression"),col = col_fun,rect_gp = gpar(type = "none"),cell_fun = cell_fun,row_names_gp = gpar(fontsize = 5),row_km = 4,border = "black")
httest <- system.file("extdata", "htdata.RDS", package = "scRNAtoolVis")pbmc <- readRDS(httest)# add groupspbmc$groups <- rep(c('stim','control'),each = 1319)# add celltypepbmc$celltype <- Seurat::Idents(pbmc)# load markergenedata("top3pbmc.markers")# checkhead(top3pbmc.markers,3)# Seurat::DotPlot()p <- DotPlot(object = pbmc, features = top3pbmc.markers$gene)下面重新整理绘图的数据# 提取并重新整理绘图数据df<- p$dataexp_mat <- df %>%dplyr::select(-pct.exp, -avg.exp) %>%pivot_wider(names_from = id, values_from = avg.exp.scaled) %>%as.data.frame()row.names(exp_mat) <- exp_mat$features.plotexp_mat <- exp_mat[,-1] %>% as.matrix()percent_mat <- df %>%dplyr::select(-avg.exp, -avg.exp.scaled) %>%pivot_wider(names_from = id, values_from = pct.exp) %>%as.data.frame()row.names(percent_mat) <- percent_mat$features.plotpercent_mat <- percent_mat[,-1] %>% as.matrix()# 填充色设置col_fun = circlize::colorRamp2(c(-0.6, 0, 2), c("#424da7","#ffffff","#dd2b19"))# 增加细胞百分比和细胞群注释cluster <- colnames(exp_mat)column_ha <- HeatmapAnnotation(cluster = cluster,col = list(cluster = setNames(brewer.pal(9, "Paired"), unique(cluster))),na_col = "grey")# 图层设置layer_fun = function(j, i, x, y, w, h, fill){grid.rect(x = x, y = y, width = w, height = h,gp = gpar(col = NA, fill = NA))grid.circle(x=x,y=y,r= pindex(percent_mat, i, j)/100 * unit(2, "mm"),gp = gpar(fill = col_fun(pindex(exp_mat, i, j)), col = NA))}# 图例设置lgd_list = list(Legend( labels = c(0,0.25,0.5,0.75,1), title = "pt",graphics = list(function(x, y, w, h) grid.circle(x = x, y = y, r = 0 * unit(2, "mm"),gp = gpar(fill = "black")),function(x, y, w, h) grid.circle(x = x, y = y, r = 0.25 * unit(2, "mm"),gp = gpar(fill = "black")),function(x, y, w, h) grid.circle(x = x, y = y, r = 0.5 * unit(2, "mm"),gp = gpar(fill = "black")),function(x, y, w, h) grid.circle(x = x, y = y, r = 0.75 * unit(2, "mm"),gp = gpar(fill = "black")),function(x, y, w, h) grid.circle(x = x, y = y, r = 1 * unit(2, "mm"),gp = gpar(fill = "black")))))上述设置好了之后，我们开始绘制图片，先看一下气泡热图# 气泡热图hp <- Heatmap(exp_mat,name = "hp",heatmap_legend_param = list(title = "expression"),col = col_fun,rect_gp = gpar(type = "none"),layer_fun = layer_fun,row_names_gp = gpar(fontsize = 5),row_names_side = "left",row_title = NULL,row_km = 4,column_names_rot = 45,border = "black",bottom_annotation = column_ha,# 去掉行聚类树的虚线show_parent_dend_line = F)draw(hp, annotation_legend_list = lgd_list)
# 装饰行namedecorate_row_names("hp", {grid.rect(gp = gpar(fill = "#FFA50080", col = "white"))}, slice = 1)
decorate_row_names("hp", {grid.rect(gp = gpar(fill = "#FF000040", col = "white"))}, slice = 2)
decorate_row_names("hp", {grid.rect(gp = gpar(fill = "#00FF0040", col = "white"))}, slice = 3)
decorate_row_names("hp", {grid.rect(gp = gpar(fill = "#0000FF40", col = "white"))}, slice = 4)
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