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#加载R包library(ggpubr)library(ggimage)library(ggplot2)library(Seurat)#设置比较-两两比较my_comparisons <- list(c("GM", "BM"))#单个featuresVlnPlot(human_data, features = "ANXA1", group.by = "group")&theme_bw()&theme(axis.title.x = element_blank(),axis.text.x = element_text(color = 'black',face = "bold", size = 12),axis.text.y = element_text(color = 'black', face = "bold"),axis.title.y = element_text(color = 'black', face = "bold", size = 15),panel.grid.major = element_blank(),panel.grid.minor = element_blank(),panel.border = element_rect(color="black",size = 1.2, linetype="solid"),panel.spacing = unit(0.12, "cm"),plot.title = element_text(hjust = 0.5, face = "bold.italic"),legend.position = 'none')&stat_compare_means(method="t.test",hide.ns = F,comparisons = my_comparisons,label="p.signif",bracket.size=0.8,tip.length=0,size=6)&scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))&scale_fill_manual(values = c("#FF5744","#208A42"))
#多个featuresVlnPlot(human_data, features = c("ANXA1","S100A8"), group.by = "group")&theme_bw()&theme(axis.title.x = element_blank(),axis.text.x = element_text(color = 'black',face = "bold", size = 12),axis.text.y = element_text(color = 'black', face = "bold"),axis.title.y = element_text(color = 'black', face = "bold", size = 15),panel.grid.major = element_blank(),panel.grid.minor = element_blank(),panel.border = element_rect(color="black",size = 1.2, linetype="solid"),panel.spacing = unit(0.12, "cm"),plot.title = element_text(hjust = 0.5, face = "bold.italic"),legend.position = 'none')&stat_compare_means(method="t.test",hide.ns = F,comparisons = my_comparisons,label="p.signif",bracket.size=0.8,tip.length=0,size=6)&scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))&scale_fill_manual(values = c("#FF5744","#208A42"))
#三组，多个features,两两比较my_comparisons1 <- list(c("HC", "EEC"))my_comparisons2 <- list(c("EEC", "AEH"))my_comparisons3 <- list(c("HC","AEH"))#设置x轴样本顺序Idents(uterus) <- "orig.ident"Idents(uterus) <- factor(Idents(uterus), levels = c("HC","AEH","EEC"))VlnPlot(uterus, features = c("TXNIP","CXCL1","CCL5","FTH1"), ncol = 2)&theme_bw()&theme(axis.title.x = element_blank(),axis.text.x = element_text(color = 'black',face = "bold", size = 12),axis.text.y = element_text(color = 'black', face = "bold"),axis.title.y = element_text(color = 'black', face = "bold", size = 15),panel.grid.major = element_blank(),panel.grid.minor = element_blank(),panel.border = element_rect(color="black",size = 1.2, linetype="solid"),panel.spacing = unit(0.12, "cm"),plot.title = element_text(hjust = 0.5, face = "bold.italic"),legend.position = 'none')&stat_compare_means(method="t.test",hide.ns = F,comparisons = c(my_comparisons1,my_comparisons2,my_comparisons3),label="p.signif",bracket.size=0.8,tip.length=0,size=6)&scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))&scale_fill_manual(values = c("#FF5744","#208A42", "#FCB31A"))
函数完整版已提前发布微信VIP群，请自行下载：我们先看看函数主体：
https://www.bilibili.com/video/BV1rGWkeMEwd/?spm_id_from=333.999.0.0&vd_source=05b5479545ba945a8f5d7b2e7160ea34
ks_VlnExp(object = human_data, group="group",group_order=c("BM","GM"),features="ANXA1",comparisons=list(c("GM", "BM")))
ks_VlnExp(object = human_data, group="group",group_order=c("BM","GM"),features="ANXA1",comparisons=list(c("GM", "BM")),cols=c("#E22C28","#0D6EBA"))
ks_VlnExp(object = uterus, group="orig.ident",group_order=c("HC","AEH","EEC"),features="ANXA1",comparisons=c(my_comparisons1,my_comparisons2,my_comparisons3))
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