【原】單細胞marker基因平均表達量熱圖

TS的美夢 2022-12-14 發(fā)布于重慶

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單細胞marker gene熱圖我們之前做過，也進行過改造：

單細胞基因可視化之熱圖改造修飾1

單細胞基因可視化之熱圖的根本改造2

但是那都是將所有細胞展現(xiàn)出來，最近有小伙伴問道如下的文獻圖，簡單明了的一種細胞一列進行marker gene表達展示。這個圖其實就是展示了平均的細胞表達量而已。我們簡單做一下。此外，順便復現(xiàn)下基因注釋。

（reference：Dissecting the transcriptome landscape of the human fetal neural retina and retinal pigment epithelium by single-cell RNA-seq analysis）

首先我們得到marker gene：

library(Seurat)human_data <- readRDS("D:/KS/human_data.rds")DefaultAssay(human_data) <- "RNA"all.markers  <- FindAllMarkers(human_data,                                only.pos = TRUE,                                min.pct = 0.25,                                logfc.threshold = 0.75)

選擇需要的marker gene進行展示，平均表達量使用seurat自帶函數(shù)AverageExpression進行計算。熱圖使用Complexheatmap做即可。

#計算平均表達量gene_cell_exp <- AverageExpression(human_data,                                   features = gene,                                   group.by = 'celltype',                                   slot = 'data') gene_cell_exp <- as.data.frame(gene_cell_exp$RNA)
#complexheatmap作圖library(ComplexHeatmap)#頂部細胞類型注釋df <- data.frame(colnames(gene_cell_exp))colnames(df) <- 'class'top_anno = HeatmapAnnotation(df = df,#細胞名/cluster                             border = T,                             show_annotation_name = F,                             gp = gpar(col = 'black'),                             col = list(class = c('Macrophage'="#9ECABE",                                                     'T cell'="#F6F5B4",                                                     'mDC'="#2F528F",                                                     "Neutrophil"="#E3AD68",                                                     "Mast"="#ACD45E")))#顏色設置#數(shù)據(jù)標準化縮放一下marker_exp <- t(scale(t(gene_cell_exp),scale = T,center = T))Heatmap(marker_exp,        cluster_rows = F,        cluster_columns = F,        show_column_names = F,        show_row_names = T,        column_title = NULL,        heatmap_legend_param = list(          title=' '),        col = colorRampPalette(c("#0000EF","black","#FDFE00"))(100),        border = 'black',        rect_gp = gpar(col = "black", lwd = 1),        row_names_gp = gpar(fontsize = 10),        column_names_gp = gpar(fontsize = 10),        top_annotation = top_anno)

重點知識來了，為熱圖行名添加分屏注釋：

col_cluster <- setNames(c(rep("#9ECABE",5), rep("#F6F5B4",6),                          rep("#2F528F",5), rep("#E3AD68",5),                          rep("#ACD45E",4)),                        rownames(marker_exp))#設置對應標簽顏色
row_info = rowAnnotation(foo = anno_text(rownames(marker_exp),                               location = 0,                               just = "left",                              gp = gpar(fill = col_cluster,                                         col = "black"),                              width = max_text_width(rownames(marker_exp))*1.2))

Heatmap(marker_exp,        cluster_rows = F,        cluster_columns = F,        show_column_names = F,        show_row_names = T,        column_title = NULL,        heatmap_legend_param = list(          title=' '),        col = colorRampPalette(c("#0000EF","black","#FDFE00"))(100),        border = 'black',        rect_gp = gpar(col = "black", lwd = 1),        row_names_gp = gpar(fontsize = 10),        column_names_gp = gpar(fontsize = 10),        top_annotation = top_anno)+row_info