R语言ggplot2绘制箱线图 / 四六文摘

欢迎来到医科研，这里是白介素2的读书笔记，跟我一起聊临床与科研的故事, 生物医学数据挖掘，R语言，TCGA、GEO数据挖掘。

R语言ggplot2绘制箱线图

差异基因与基因交集

if(T){ require(tidyverse) AS_gene<-read.table("F:/Bioinfor_project/Breast/AS_research/AS/result/BRCA_marker_cox_single_all.txt",header =T,sep = "\t") AS_gene[1:5,1:5] final_DEmRNA<-read.csv("F:/Bioinfor_project/Breast/AS_research/AS/result/TNBC_DEmRNA.csv",header=T,row.names = 1) DEG_2<-final_DEmRNA %>% rownames_to_column("genename") hubgene<-intersect(AS_gene$symbol,DEG_2$genename) }

清洗数据-进一步探索

if(T){ require(dplyr) ## 提取已标准化的数据 mRNA_exp<-read.csv(file="F:/Bioinfor_project/Breast/AS_research/AS/result/TNBC_mRNA_exp_log.csv",header = T,row.names = 1) load("F:/Bioinfor_project/Breast/TCGA/RNA-seq-model/BRCA_all.Rdata") BRCA_all[1:5,1:5] dim(BRCA_all)## 24491 1200 head(phe) colnames(phe)


##

mRNA_exp[1:5,1:5]

dim(mRNA_exp)

data_exp<-mRNA_exp[hubgene,]

## 提取匹配的临床信息

data_phe<-phe %>%

  filter(ID %in% colnames(mRNA_exp))

## 合并临床信息与表达数据 data<-data_exp %>% t() %>% as.data.frame() %>% ##行名变列名 rownames_to_column(var = "ID") %>% as_tibble() %>% ## 合并临床信息与表达数据 inner_join(data_phe,by="ID") %>% ## 增加分组信息 mutate(group=ifelse(substring(colnames(mRNA_exp),14,15)=="01","TNBC","Normal")) %>% ## 分组提前 dplyr::select(ID,group,everything()) group=factor(c(rep(1,115),rep(0,113))) head(data) #save(data,file = "F:/Bioinfor_project/Breast/AS_research/AS/result/hubgene.Rdata") } ## # A tibble: 6 x 22 ## ID group CCL14 HBA1 CCL16 TUBB3 PAM50 Os_time OS_event RFS_time ## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <fct> <int> <int> <int> ## 1 TCGA~ TNBC 3.37 0 0 5.94 Basal 967 1 NA ## 2 TCGA~ TNBC 4.97 3.39 0 6.00 Basal 584 0 NA ## 3 TCGA~ TNBC 4.77 0 0 5.04 Basal 2654 0 NA ## 4 TCGA~ TNBC 4.19 3.74 2.84 5.13 Basal 754 1 NA ## 5 TCGA~ TNBC 0 0 0 5.65 Basal 2048 0 2048 ## 6 TCGA~ TNBC 5.34 0 4.07 6.04 Basal 1027 0 1027 ## # ... with 12 more variables: RFS_event <int>, age <int>, ER <fct>, ## # PR <fct>, gender <fct>, HER2 <fct>, Margin_status <fct>, Node <int>, ## # M_stage <fct>, N_stage <fct>, T_stage <fct>, `Pathologic stage` <fct>

载入数据

数据清洗-gather-spread

load(file = "F:/Bioinfor_project/Breast/AS_research/AS/result/hubgene.Rdata") head(data) ## # A tibble: 6 x 22 ## ID group CCL14 HBA1 CCL16 TUBB3 PAM50 Os_time OS_event RFS_time ## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <fct> <int> <int> <int> ## 1 TCGA~ TNBC 3.37 0 0 5.94 Basal 967 1 NA ## 2 TCGA~ TNBC 4.97 3.39 0 6.00 Basal 584 0 NA ## 3 TCGA~ TNBC 4.77 0 0 5.04 Basal 2654 0 NA ## 4 TCGA~ TNBC 4.19 3.74 2.84 5.13 Basal 754 1 NA ## 5 TCGA~ TNBC 0 0 0 5.65 Basal 2048 0 2048 ## 6 TCGA~ TNBC 5.34 0 4.07 6.04 Basal 1027 0 1027 ## # ... with 12 more variables: RFS_event <int>, age <int>, ER <fct>, ## # PR <fct>, gender <fct>, HER2 <fct>, Margin_status <fct>, Node <int>, ## # M_stage <fct>, N_stage <fct>, T_stage <fct>, `Pathologic stage` <fct> require(cowplot)

调整清洗数据至想要的格式

require(tidyverse) require(ggplot2) require(ggsci) ## Loading required package: ggsci mydata<-data %>% ## 基因表达数据gather,gather的范围应调整 gather(key="gene",value="Expression",CCL14:TUBB3) %>% ## dplyr::select(ID,gene,Expression,everything()) head(mydata) ## # A tibble: 6 x 20 ## ID gene Expression group PAM50 Os_time OS_event RFS_time RFS_event ## <chr> <chr> <dbl> <chr> <fct> <int> <int> <int> <int> ## 1 TCGA~ CCL14 3.37 TNBC Basal 967 1 NA NA ## 2 TCGA~ CCL14 4.97 TNBC Basal 584 0 NA NA ## 3 TCGA~ CCL14 4.77 TNBC Basal 2654 0 NA NA ## 4 TCGA~ CCL14 4.19 TNBC Basal 754 1 NA NA ## 5 TCGA~ CCL14 0 TNBC Basal 2048 0 2048 0 ## 6 TCGA~ CCL14 5.34 TNBC Basal 1027 0 1027 0 ## # ... with 11 more variables: age <int>, ER <fct>, PR <fct>, gender <fct>, ## # HER2 <fct>, Margin_status <fct>, Node <int>, M_stage <fct>, ## # N_stage <fct>, T_stage <fct>, `Pathologic stage` <fct>

绘制简单箱线图

P<-mydata %>% ## 确定x,y ggplot(aes(x = gene, y = Expression, fill = group)) + geom_boxplot(alpha=0.7) + scale_y_continuous(name = "Expression")+ scale_x_discrete(name = "Gene") + ggtitle("Boxplot of hub gene") + theme_bw() + theme(plot.title = element_text(size = 14, face = "bold"), text = element_text(size = 12), axis.title = element_text(face="bold"), axis.text.x=element_text(size = 11)) P

ggsci调色

调用scale_fill_lancet，调色lancet配色

p2<-P+scale_fill_lancet() p2 #ggsave(p2,filename = "hub_gene_boxplot.pdf",width = 5,height = 5)

分面图形

facet_wrap()

P<-mydata %>% ## 确定x,y ggplot(aes(x = group, y = Expression, fill = group)) + geom_boxplot(alpha=0.7) + scale_y_continuous(name = "Expression")+ scale_x_discrete(name = "group") + ggtitle("Boxplot of hub gene") + theme_bw() + theme(plot.title = element_text(size = 14, face = "bold"), text = element_text(size = 12), axis.title = element_text(face="bold"), axis.text.x=element_text(size = 11)) P

p3<-P+scale_fill_lancet()+facet_wrap(~gene) p3 #ggsave(p3,filename = "hub_gene_boxplot_facet.pdf",width = 5,height = 5)

加入其它变量并分面-PAM50

p<-mydata %>% ## 筛选数据,选定x,y filter(group=="TNBC" & PAM50!="NA") %>% ggplot(aes(x = PAM50, y = Expression, fill = PAM50)) + geom_boxplot(alpha=0.7) + scale_y_continuous(name = "Expression")+ scale_x_discrete(name = "PAM50") + ggtitle("Boxplot of hub gene") + theme_bw() + theme(plot.title = element_text(size = 14, face = "bold"), text = element_text(size = 12), axis.title = element_text(face="bold"), axis.text.x=element_text(size = 11)) p+scale_fill_lancet()+ facet_wrap(~gene)##分面变量

for循环实现批量绘图

for循环：命名空对象list 配合do.call函数

library(gridExtra) ## ## Attaching package: 'gridExtra' ## The following object is masked from 'package:dplyr': ## ## combine library(ggplot2) p <- list() genename<-hubgene for (j in genename) { p[[j]] <- ggplot(data=data, aes_string(x=group, y=j)) + geom_boxplot(alpha=0.7,aes(fill=group)) + scale_y_continuous(name = "Expression")+ scale_x_discrete(name = j) + ggtitle(paste0("boxlot of ",j) ) +##ggtitle指定 theme_bw() + theme(plot.title = element_text(size = 14, face = "bold"), text = element_text(size = 12), axis.title = element_text(face="bold"), axis.text.x=element_text(size = 11))+ scale_fill_lancet() #ggsave(sprintf("boxplot%s.pdf",j),width=5,height=5,onefile=T) } do.call(grid.arrange, c(p, ncol=2))

R语言ggplot2绘制箱线图