手把手教你绘制多个基因表达值小提琴图---百味科研芝士

数据准备#set your work directory data<-read.csv(file = "data.csv",header = T,sep = ",") colnames(data)<-c("gene",colnames(data)[-1]) test<-data[1:5,1:5] View(test) ### data<-aggregate(data[,2:ncol(data)],by=list(data$gene),FUN = mean,na.rm=T)##重复基因求平均值 genename<-data$Group.1 rownames(data)<-genename data<-data[,-1] sampleID<-colnames(data) data<-apply(data, 1, as.numeric) rownames(data)<-sampleID ##分组信息构造 group<-c(rep("N",14),rep("DCIS",9),rep("IBC",9),rep("NS",14),rep("DCISS",11),rep("IBCS",9)) length(group)==dim(data)[[1]]##确认信息匹配 ## [1] TRUE data<-as.data.frame(data) data$group<-group table(data$group) ## ## DCIS DCISS IBC IBCS N NS ## 9 11 9 9 14 14 data[1:5,1:5]##行为sample名 列为gene ## ACVR1B CXCR4 IL11 INHBA LTB ## N1 3.812931 3.669153 2.922135 2.916415 3.072535 ## N2 2.968409 4.270815 2.988273 3.068690 2.757790 ## N3 3.806364 4.327977 2.811002 2.546459 2.897796 ## N4 3.621140 3.698909 2.815539 3.278493 2.785017 ## N5 3.812910 4.214652 2.814199 2.800704 2.916013 整合小提琴图# http://www.sthda.com/english/articles/24-ggpubr-publication-ready-plots/ library(ggpubr) ## Loading required package: ggplot2 ## Loading required package: magrittr my_comparisons <- list(c("IBC", "DCIS"), c("N", "DCIS"), c("IBCS", "DCISS"),c("NS" ,"DCISS"))##分组设定 #my_comparisons <- list( c("IBC", "DCIS"), c("N", "DCIS") )##分组设定 e<-data %>% #dplyr::filter(group %in% c("IBC","N","DCIS")) %>% ggviolin(x = "group", y = c(colnames(data)[1:6]), fill = "group", combine = T, #palette = c("#00AFBB", "#E7B800", "#FC4E07"),## ylab="Normalized Expression", add = "boxplot", add.params = list(fill = "white")) e+stat_compare_means(method = "t.test", #label = "p.signif",##星号设置 comparisons = my_comparisons) #theme_gray(base_size = 14)##background ggsave("all_violin.pdf", width = 10, height = 8) 小提琴图DCIS VS. IBC/Nlibrary(ggpubr) my_comparisons <- list( c("IBC", "DCIS"), c("N", "DCIS") )##分组设定 e<-data %>% dplyr::filter(group %in% c("IBC","N","DCIS")) %>% #筛选行 ggviolin(x = "group", y = c(colnames(data)[1:6]), fill = "group", combine = T, #palette = c("#00AFBB", "#E7B800", "#FC4E07"),##颜色设置 ylab="Normalized Expression", add = "boxplot", add.params = list(fill = "white")) e+stat_compare_means(method = "t.test", #label = "p.signif",##星号设置 comparisons = my_comparisons) #theme_gray(base_size = 14)##background ggsave("group1_violin.pdf", width = 10, height = 8) 小提琴图DCISS VS. IBCS/NSlibrary(ggpubr) my_comparisons <- list(c("IBCS","DCISS"),c("NS","DCISS"))##分组设定 e<-data %>% dplyr::filter(group %in% c("IBCS","NS","DCISS")) %>% ggviolin(x = "group", y = c(colnames(data)[1:6]), fill = "group", combine = T, #palette = c("#00AFBB", "#E7B800", "#FC4E07"),## ylab="Normalized Expression", add = "boxplot", add.params = list(fill = "white")) e+stat_compare_means(comparisons = my_comparisons) ggsave("group2_violin.pdf", width = 10, height = 8) 箱线图my_comparisons <- list(c("IBC", "DCIS"), c("N", "DCIS"), c("IBCS", "DCISS"),c("NS" ,"DCISS"))##分组设定 e<-data %>% #dplyr::filter(group %in% c("IBCS","NS","DCISS")) %>% ggboxplot(x = "group", y = c(colnames(data)[1:6]), fill = "group", combine = T, #palette = c("#00AFBB", "#E7B800", "#FC4E07"),## ylab="Normalized Expression") e+stat_compare_means(comparisons = my_comparisons) ggsave("group2_boxplot.pdf", width = 10, height = 8) ---来自腾讯云社区的---百味科研芝士