生信技能树2021生信入门线上课笔记，需要结合课程讲解服用
1.使用循环，对iris的1到4列分别画点图（plot）
方案1：我的答案
> library(patchwork)
> library(ggplot2)
> p=list()
> for(i in 1:4) {
+ p[[i]] = ggplot(data = iris, aes(x = 1:nrow(iris), y = !!iris[, i])) +
+ geom_point(aes(color = Species))+
+ labs(x = "Number", y = colnames(iris)[i], title = "")
+ }
> n=wrap_plots(p,nrow=2,guides = 'collect')
> n
> ggsave(n,filename = "practice1.png")
方案1.png
方案2：老师的参考答案
par(mfrow = c(2,2))
for(i in 1:4){
plot(iris[,i],col = iris[,5])
}
方案2.png
2.生成一个随机数（rnorm）组成的10行6列的矩阵，列名为sample1，sample2….sample6，行名为gene1，gene2…gene10，分组为sample1、2、3属于A组，sample4、5、6属于B组。用循环对每个基因画ggplot2箱线图，并尝试拼图。
方案1：导出成单独的图再拼图
m=matrix(rnorm(1:60),nrow = 10);m
colnames(m)=paste0('sample',1:6)
rownames(m)=paste0('gene',1:10)
n=t(m);n
n=as.data.frame(n)
class(n)
#增加列
library(dplyr)
n=mutate(n,group=rep(c('A','B'),each=3));n
#画图
library(ggplot2)
plot_list =list()
for (i in 1:(ncol(n)-1)) {
x = ggplot(data=n,aes(x=group, y=n[,i],fill=group)) +
stat_boxplot(geom ='errorbar', width = 0.3)+
geom_boxplot( width = 0.3)
plot_list[[i]] = x+labs(x = "Group", y = colnames(n)[i], title = "")
}
#保存图
for (i in 1:(ncol(n)-1)) {
file_name = paste("practice2_", i, ".tiff", sep="")
tiff(file_name)
print(plot_list[[i]])
dev.off()
}
方案1.png
方案2：老师的答案参考
#生成矩阵
exp = matrix(rnorm(60),nrow = 10)
colnames(exp) <- paste0("sample",1:6)
rownames(exp) <- paste0("gene",1:10)
exp[1:4,1:4]
#dat = cbind(t(exp),group = rep(c("A","B"),each = 3))
dat = data.frame(t(exp))
dat = mutate(dat,group = rep(c("A","B"),each = 3))
p = list()
library(ggplot2)
for(i in 1:(ncol(dat)-1)){
p[[i]] = ggplot(data = dat,aes_string(x = "group",y=colnames(dat)[i]))+
geom_boxplot(aes(color = group))+
geom_jitter(aes(color = group))+
theme_bw()
}
library(patchwork)
wrap_plots(p,nrow = 2,guides = "collect")
# 分面也行的。
exp = matrix(rnorm(60),nrow = 10)
colnames(exp) <- paste0("sample",1:6)
rownames(exp) <- paste0("gene",1:10)
exp[1:4,1:4]
dat = data.frame(t(exp))
dat = mutate(dat,group = rep(c("A","B"),each = 3))
library(tidyr)
dat2 = gather(dat,key = "gene",value = "expression",-group)
ggplot(data = dat2)+
geom_boxplot(aes(x = group,y = expression,color = group))+
theme_bw()+
facet_wrap(~gene,nrow = 2)
image.png
分面.png
方案3：基于老师的答案优化我的答案
#生成矩阵
m=matrix(rnorm(1:60),nrow = 10);m
colnames(m)=paste0('sample',1:6)
rownames(m)=paste0('gene',1:10)
n=t(m);n
n=as.data.frame(n)
class(n)
#增加列
library(dplyr)
n=mutate(n,group=rep(c('A','B'),each=3));n
#画图
library(ggplot2)
plot_list =list()
for (i in 1:(ncol(n)-1)) {
plot_list[[i]] = ggplot(data=n,aes(x=group, y=!!n[,i],fill=group)) +
stat_boxplot(geom ='errorbar', width = 0.3)+
geom_boxplot( width = 0.3)+
labs(x = "Group", y = colnames(n)[i], title = "")
}
#拼图
library(patchwork)
wrap_plots(plot_list,nrow = 2,guides = "collect")
方案3.png
- 模拟出几个类似的文件，用R实现批量重命名
> folder<-setwd('D:/Desktop/practice/test')
> files<-list.files(folder)
> for (f in files){
+ newname<-sub('test','practice',f)
+ file.rename(f,newname)
+ }
dir()
[1] "practice2_1.png" "practice2_10.png"
[3] "practice2_2.png" "practice2_3.png"
[5] "practice2_4.png" "practice2_5.png"
[7] "practice2_6.png" "practice2_7.png"
[9] "practice2_8.png" "practice2_9.png"
修改前.png
修改后.png
