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setwd('D:\\KS项目\\公众号文章\\单细胞marker基因密度图')library(Seurat)library(Nebulosa)library(ggnetwork)library(dplyr)markers <- FindAllMarkers(mouse_data, logfc.threshold = 0.5, min.pct = 0.5)markers_plot <- markers %>%group_by(cluster) %>%slice(1:2)
plot_density(mouse_data, features = c("Ltf"),pal = 'magma', raster = T, size = 0.8) &theme_blank()&#这个是ggnetwork里面的主题，可以去掉所有ggplot背景theme(legend.frame = element_rect(colour = "black"),legend.ticks = element_line(colour = "black", linewidth = 0),legend.key.width = unit(0.3, "cm"),legend.key.height = unit(0.8, "cm"),legend.title = element_text(color = 'black', face = "bold", size=8))
plot_density(mouse_data, features = c("Ltf"),pal = 'magma', raster = T, size = 0.8) &theme_blank()&theme(panel.background = element_rect(fill = "black"))&theme(legend.frame = element_rect(colour = "black"),legend.ticks = element_line(colour = "black", linewidth = 0),legend.key.width = unit(0.3, "cm"),legend.key.height = unit(0.8, "cm"),legend.title = element_text(color = 'black', face = "bold", size=8))
###批量作图plist <- list()for (i in 1:nrow(markers_plot)) {p = plot_density(mouse_data, features = markers_plot$gene[i],pal = 'magma', raster = F, size = 0.8) &theme_blank()&theme(legend.frame = element_rect(colour = "black"),legend.ticks = element_line(colour = "black", linewidth = 0),legend.key.width = unit(0.3, "cm"),legend.key.height = unit(0.6, "cm"),legend.title = element_text(color = 'black', face = "bold", size=8))plist[[i]] <- p}#拼图library(cowplot)plot_grid(plotlist = plist, ncol = 4)
plist1 <- list()for (i in 1:nrow(markers_plot)) {p = plot_density(mouse_data, features = markers_plot$gene[i],pal = 'magma', raster = F, size = 0.8) &theme_blank()&theme(panel.background = element_rect(fill = "black"))&theme(legend.frame = element_rect(colour = "black"),legend.ticks = element_line(colour = "black", linewidth = 0),legend.key.width = unit(0.8, "cm"),legend.key.height = unit(0.3, "cm"),legend.title = element_text(color = 'black', face = "bold", size=8))&theme(plot.title = element_blank())&theme(legend.position = "top")&annotate("text", x = 0, y = Inf,label = markers_plot$gene[i], vjust = 1.5,size = 6, color='white')plist1[[i]] <- p}#拼图library(cowplot)plot_grid(plotlist = plist1, ncol = 4)
library(ggunchull)plot_density(mouse_data, features = c("Ltf"),pal = 'magma', raster = T, size = 0.8) &theme_blank()&theme(panel.background = element_rect(fill = "black"))&theme(legend.frame = element_rect(colour = "black"),legend.ticks = element_line(colour = "black", linewidth = 0),legend.key.width = unit(0.3, "cm"),legend.key.height = unit(0.8, "cm"),legend.title = element_text(color = 'black', face = "bold", size=8))&theme(plot.title = element_blank())&annotate("text", x = 0, y = Inf,label = "Ltf", vjust = 1.5,size = 6, color='white')&stat_unchull(alpha=0.25,size=0.25,lty=2,color='white',nbin = 400,nsm = 5,qval = 0.8,sfac = 1.4)
single_CM_density(object = mouse_data,features = "Ltf",night = T)
#2黑夜模式，只选择需要的celltype，我这里选择PMN(7），聚类好#设置这个模式，需要设置参数identssingle_CM_density(object = mouse_data,features = "Ltf",night = T,idents = "celltype",label_celltype = "PMN(7)")
#正常模式#unchull=F,不需要框线single_CM_density(object = mouse_data,features = "Ltf",night = F)#unchull=T,需要框线single_CM_density(object = mouse_data,features = "Ltf",night = F,unchull = T)
#批量出图plist2 <- list()for (i in 1:nrow(markers_plot)) {p = single_CM_density(object = mouse_data,features = markers_plot$gene[i],night = T)plist2[[i]] <- p}#拼图library(cowplot)plot_grid(plotlist = plist2, ncol = 4)
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