Telomere-to-mitochondria signalling by ZBP1 mediates replicative crisis
https://www.nature.com/articles/s41586-023-05710-8
s41586-023-05710-8.pdf
大部分图的原始数据都有,争取把有原始数据的图都用R语言来复现一下
41586_2023_5710_MOESM4_ESM (1).xlsx
今天的推文复现一下论文中的Fig1a
image.png
image.png
library(tidyverse)
fig1a<-read_delim("data/20230521/Figure1a.txt",
delim = " ")
library(ggplot2)
ggplot()+
geom_point(data=fig1a,
aes(x=log2(FC_Replicate_1),
y=log2(FC_Replicate_2)),
size=10,
shape=21,
fill="#f1f1f1",
color="black")+
theme_bw()
image.png
这里我的处理方式是把想要映射颜色的点单独挑出来,然后再叠加一层
geneSelected<-c("ZBP1","IFNB1","CGAS","IFNAR1","STING","IFNAR2")
match(geneSelected,fig1a %>% pull(Gene))
本来是想用上面的代码把图例基因的数据匹配出来,但是有些基因名没有找到,这里我就随机选择几个了
fig1a %>%
sample_n(6) -> fig1adf
ggplot()+
geom_point(data=fig1a,
aes(x=log2(FC_Replicate_1),
y=log2(FC_Replicate_2)),
size=10,
shape=21,
fill="#f1f1f1",
color="black")+
theme_bw()+
geom_point(data=fig1adf,
aes(x=log2(FC_Replicate_1),
y=log2(FC_Replicate_2),
fill=Gene),
size=10,
shape=21)
image.png
ggplot()+
geom_point(data=fig1a,
aes(x=log2(FC_Replicate_1),
y=log2(FC_Replicate_2)),
size=10,
shape=21,
fill="#f1f1f1",
color="black")+
theme_classic()+
geom_point(data=fig1adf,
aes(x=log2(FC_Replicate_1),
y=log2(FC_Replicate_2),
fill=Gene),
size=10,
shape=21)+
scale_x_continuous(breaks = c(2,3,4))+
scale_y_continuous(breaks = c(2,3,4))+
theme(legend.position = "top",
legend.text = element_text(face="italic"))+
guides(fill=guide_legend(ncol = 2,title = NULL))+
labs(x="log2[fold change]\nReplicate 1",
y="log2[fold change]\nReplicate 2")
image.png
这里既要把2设置成下标,又要实现文本分行,我暂时想不到用什么办法来实现了
ggplot()+
geom_point(data=fig1a,
aes(x=log2(FC_Replicate_1),
y=log2(FC_Replicate_2)),
size=5,
shape=21,
fill="#f1f1f1",
color="black")+
theme_classic()+
geom_point(data=fig1adf,
aes(x=log2(FC_Replicate_1),
y=log2(FC_Replicate_2),
fill=Gene),
size=5,
shape=21)+
scale_x_continuous(breaks = c(2,3,4))+
scale_y_continuous(breaks = c(2,3,4))+
theme(legend.position = "top",
legend.text = element_text(face="italic"))+
guides(fill=guide_legend(ncol = 2,title = NULL))+
labs(x="log2[fold change]\nReplicate 1",
y="log2[fold change]\nReplicate 2") -> p1
ggplot()+
geom_point(data=fig1a,
aes(x=log2(FC_Replicate_1),
y=log2(FC_Replicate_2)),
size=5,
shape=21,
fill="#f1f1f1",
color="black")+
theme_classic()+
geom_point(data=fig1adf,
aes(x=log2(FC_Replicate_1),
y=log2(FC_Replicate_2),
fill=Gene),
size=5,
shape=21)+
scale_x_continuous(breaks = c(2,3,4))+
scale_y_continuous(breaks = c(2,3,4))+
theme(legend.position = "top",
legend.text = element_text(face="italic"))+
guides(fill=guide_legend(ncol = 2,title = NULL))+
labs(x="log2[fold change]\nReplicate 1",
y="log2[fold change]\nReplicate 2")+
scale_fill_manual(values = c("#ef7a79","#edd08e","#29b473",
"#000000","#094c8b","#92d4f6")) -> p2
library(patchwork)
p1+p2
image.png
推文记录的是自己的学习笔记,内容可能会存在错误,请大家批判着看,欢迎大家指出其中的错误
示例数据和代码可以给推文点赞,然后点击在看,最后留言获取
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