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函数参数如下：增加的参数首先第一个rownames_anno，传入一个向量，是需要标记的基因，如果基因过多的时候，不适宜全部展示，show_row_names选择F。第二个就是anno_enrich，默认F，如果需要添加富集结果的注释，选择T，需要注意，函数并未提供富集，富集结果需要手动展示。对应的注释传入enrich_terms，是一个list，此外，添加富集注释，一定要设置cluster_order，而且cluster_gene_length要与cluster_order一致。
library(Seurat)library(ComplexHeatmap)library(dplyr)library(circlize)library(rlang)library(grDevices)source('./ks_single_gene_heatmap.R')Epi_cells$cluster <- as.character(Epi_cells$cluster)#heatmappdf('./nmf_heat1.pdf', height = 8,width = 8)ks_single_gene_heatmap(object=Epi_cells,assay = 'RNA',genes = cluster_gene$gene,bar = c("cluster"),show_rownames = F,heat_cols = colorRampPalette(c('#FFF7F3', '#FDE0DD', '#FCC5C0', '#FA9FB5', '#F768A1','#DD3497', '#AE017E', '#7A0177', '#49006A'))(100),rownames_anno = c("NME2","GLIS3","DNAI1","PTPRC","GABARAP","PARD3","CDHR3","SRGN","PRDX2","MECOM","CFAP299","FYN","HINT1","CFAP157","CCL5"))dev.off()
#标注富集结果text2 = list("1"=c("labyrinthine layer morphogenesis","neural tube closure","epithelial tube morphogenesis"),"2" =c("positive regulation of cell adhesion","Cell adhesion molecules","Inflammatory response pathway"),"3"=c("Signaling by MET","PI3K-Akt signaling pathway"),"4"=c("cellular response to abiotic stimulus","cellular response to environmental stimulus"))pdf('./nmf_heat2.pdf', height = 8,width = 12)ks_single_gene_heatmap(object=Epi_cells,assay = 'RNA',genes = cluster_gene$gene, bar = c("cluster"),show_rownames = F,rownames_anno = c("NME2","GLIS3","DNAI1","PTPRC","GABARAP","PARD3","CDHR3","SRGN","PRDX2","MECOM","CFAP299","FYN","HINT1","CFAP157","CCL5"),heat_cols = colorRampPalette(c('#FFF7F3', '#FDE0DD', '#FCC5C0', '#FA9FB5', '#F768A1','#DD3497', '#AE017E', '#7A0177', '#49006A'))(100),anno_enrich=T,cluster_gene_length=c(50,50,50,50),enrich_terms = text2,cluster_order = c("1","2","3","4"))dev.off()
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