R语言绘制SNP位置 r语言绘制图

项目要求：

1. select 5 figures from “Nature”（从自然杂志中选择5张图表）
2. draw the same figure with fake data（用假数据绘制相同的图形）
3. submit （1）R code + randata （确保复制过来能直接用）（2）report original figure （把原文出处标注出）

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一、韦恩图

#韦恩图
install.packages("VennDiagram")
library(VennDiagram)
getwd()
setwd('E:/大三上/R语言/picture')
getwd()

setwd("E:/大三上/R语言/picture")

venn<-venn.diagram(list(A = 1:150, B =c(121:170,300:320),C=c(20:40,141:200)),
                    filename=NULL,  
                    col = "black",#表示对应圆周的颜色
                    fill = c("cornflowerblue", "green", "yellow"),#表示各个集合对应的圆填充颜色
                    alpha = 0.4,
                    cat.col = c("darkblue", "darkgreen", "orange"), #表示集合名称的显示颜色
                    cat.cex = 1.5,
                    rotation.degree = 0,
                    lwd=1,#设定圆弧的宽度
                    lty=1,
                    main = "韦恩图");#设定圆弧的线型
grid.draw(venn)

 二、折线图

#折线图
par(pch=22, col="red") # 设置绘图符号和颜色，下图表示的就是绘图符号 
par(mfrow=c(2,2)) # 设置绘图版面，将画布设置成2行4列的格式，共8个绘图区域
data=read.table("E:/大三上/R语言/zhexian.txt",header = T,sep = "\t")
data
plot(data$x0,data$y1,
     main="折线图1",#自定义标题
     sub="例1",#副标题
     xlab="year",ylab="weight",#X、Y轴标题
     col="red",
     pch=3,#点类型参数	
     lwd=2,#点边框粗细参数
     type='s')
#lines(data$x0,data$y2,pch=2,cex=1.2,lwd=2,col="blue",type='o')
plot(data$x0,data$y2,
     main="折线图2",#自定义标题
     sub="例2",#副标题
     xlab="year",ylab="weight",#X、Y轴标题
     col="blue",
     pch=3,#点类型参数	
     lwd=2,#点边框粗细参数
     type='s')
plot(data$x0,data$y3,
     main="折线图3",#自定义标题
     sub="例3",#副标题
     xlab="year",ylab="weight",#X、Y轴标题
     col="green",
     pch=3,#点类型参数	
     lwd=2,#点边框粗细参数
     type='s')
plot(data$x0,data$y4,
     main="折线图4",#自定义标题
     sub="例4",#副标题
     xlab="year",ylab="weight",#X、Y轴标题
     col="yellow",
     pch=3,#点类型参数	
     lwd=2,#点边框粗细参数
     type='s')
lines(data$x0,data$y3,pch=5,cex=1.2,lwd=2,col="green",type='o')
#lines(data$x0,data$y4,pch=5,cex=1.2,lwd=2,col="yellow",type='o')
legend("topright", 
       c("y1", "y2","y3","y4"),
       pch = c(3,2,5),
       col=c("red","blue","green","yellow"),
       bg ="white")

三、热图

install.packages("pheatmap")
library(pheatmap)
mtcars#R自带汽车想换数据
data<- as.matrix((scale(mtcars))) #归一化，转换成矩阵
pheatmap(data,
         treeheight_row=140,
         treeheight_col=11,
         cluster_cols=FALSE,#不按列聚类
         color=colorRampPalette(c("yellow","white","red"))(1000),
         border_color=NA,#方格边框颜色设置
         fontsize=10,
         fontsize_row=8,
         display_numbers=FALSE)#是否填充数字

四、柱状图

#柱状图
library(ggplot2)
now=c(153,165,146,158,163,167,180)
pre=c(130,134,126,154,123,144,145)
value.df<-data.frame(pre,now)
barplot(value.df$now)
barplot(value.df$now,
        horiz=T,#水平柱状图
        beside = FALSE,
        axes = TRUE,
        col = "red4",
        border="red",
        xlab="Numbers of Cells",ylab="value", main="value of item",
        names.arg=c(1:7))

values<-as.matrix(value.df)
values<-t(values)
values
barplot(values,
        horiz=T,
        beside = FALSE,axes = TRUE,
        
        xlab="Numbers of Cells",ylab="value", 
        names.arg=c(1:7))

五、面积图

library("gcookbook")
uspopage

#ggplot(uspopage,aes(Year,Thousands,fill=AgeGroup))+geom_area()
#ggplot(uspopage,aes(Year,Thousands,fill=AgeGroup))+geom_area(position="stack")
#ggplot(uspopage,aes(Year,Thousands,fill=AgeGroup))+geom_area(position="identity")


ggplot(uspopage,aes(Year,Thousands,fill=AgeGroup))+geom_area(position="stack",alpha=0.7)+facet_wrap(~AgeGroup)