[英]loop for generating multiple QQ-plot for normal distribution
I have a data set with multiple variables and hundreds of entries.我有一个包含多个变量和数百个条目的数据集。 The dataframe is like this (simple)
dataframe是这样的(简单)
> my_Data
# A tibble: 9 x 3
Gene Time Expression
<chr> <chr> <dbl>
1 Gene1 W1 18.8
2 Gene2 W1 13.9
3 Gene3 W1 20.9
4 Gene1 W2 9.29
5 Gene2 W2 10.9
6 Gene3 W2 12.2
7 Gene1 W3 13.8
8 Gene2 W3 23.9
9 Gene3 W3 17.4
>
I need to test for normal distribution for each combination of variables.我需要测试每个变量组合的正态分布。 I can do this using looping the qqnorm, it works perfectly and generates the plots that I need, but the main title of all plots are the same (here I used
main = "myTitle"
) and after exporting I cannot correlate each plot to which subsets.我可以使用循环 qqnorm 来做到这一点,它可以完美地工作并生成我需要的图,但是所有图的主标题都是相同的(这里我使用
main = "myTitle"
)并且在导出后我无法将每个 plot 关联到哪个子集。
here is my code这是我的代码
attach(my_Data)
my_qq = list()
for (ids in unique(my_Data$Gene)){
sub_Data = subset(x=my_Data, subset=Gene==ids)
my_qq[[ids]] = qqnorm(sub_Data$Expression, main = "myTitle", pch=19)
qqline(sub_Data$Expression, col="red", lty =2, lwd = 3)
}
1)Is there anyway that each one of my plots have a different title? 1)无论如何,我的每一个情节都有不同的标题吗? 2) Can I save them all as separate plots?
2)我可以将它们全部保存为单独的图吗?
my_Data <- data.frame(Gene=rep(c("Gene1", "Gene2", "Gene3"), 3),
Time=rep(c("W1", "W2", "W3"), each=3),
Expression=c(18.8, 13.9, 20.9, 9.29, 10.9, 12.2, 13.8, 23.9, 17.4))
for (id in unique(my_Data$Gene)){
sub_Data <- my_Data[which(my_Data$Gene == id), ]$Expression
pdf(paste0(id, ".pdf"))
qqnorm(sub_Data, main=paste("Gene =", id))
qqline(sub_Data, col="red", lty =2, lwd = 3)
dev.off()
}
pdf()
saves your image into the current working directory. pdf()
将您的图像保存到当前工作目录中。 Check this with getwd()
.用
getwd()
检查这个。
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