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[How to draw this picture] The series of pictures are all from VIP群the students' questions. The tweet is only a reproduction of the picture, and does not mean that the author agrees with the form of the picture. Students are welcome to analyze interesting pictures in the group.
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❝Han G, Yang G, Hao D, et al. 9p21 loss confers a cold tumor immune microenvironment and primary resistance to immune checkpoint therapy. Nat Commun. 2021;12(1):5606. Published 2021 Sep 23. doi:10.1038/s41467-021-25894-9
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The changes in the expression of 28 immune regulatory genes were analyzed from 9p21-WTtumor to tumor in different cancer types .9p21-loss
Reproduce results
Sample data and code collection
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drawing
# data example
library(dplyr)
data <- data.frame(type =sort(rep(paste0('cancer',LETTERS[seq(1,15)]),15)),
gene = rep(paste0('gene',1:15),15),
Log2FC = runif(225,-1,1),
pvalue = runif(225,0.000001,1))
head(data)
## plot
library(ggplot2)
p1 <- ggplot(data,aes(x=type ,y= gene)) +
geom_point(aes(size=-log10(pvalue), fill=Log2FC),
shape=21,
color="black") +
scale_fill_gradient2(name = 'Log2FC\n(Expression)',
limit = c(-1.001,1.001),
breaks = c(-1.0,-0.5,0.0,0.5,1.0),
low='#444283',
high='#943934',
mid="white",
midpoint = 0)+
scale_size_continuous(name = '-Log10 qvalue',
limit = c(-0.001,3.1),
breaks = c(0,1,2,3))+
geom_hline(yintercept=c(5.5, 10.5))+
labs(x=NULL,
y=NULL,
title = "Expression of immunomodulatory genes (9p21-Loss vs 9p21-WT)")+
theme_bw()+
theme(panel.grid = element_blank(),
legend.key = element_blank(),
plot.title = element_text(hjust = 0.5, size = 12),
axis.text =element_text(size = 10, color = "black"),
axis.text.y = element_blank(),
axis.text.x=element_text(angle=45,hjust = 0.5,vjust=0.5))
p1
# rect anotate
anotate <- data %>% distinct(gene,.keep_all = T)
head(anotate)
p2 <- ggplot(anotate,aes(x = 0,y = gene,label= gene )) +
geom_text()+
annotate("rect",
ymin = c(0.5,5.5,10.5), ymax = c(5.5,10.5,15.5),
xmin = -5, xmax = 0.7,
fill = c('#ecf7fb','#fffbe7','#ffe7df'),
alpha = 0.5)+
theme_void()
p2
# patch
library(patchwork)
library(cowplot)
p2+p1+plot_layout(nrow= 1,
width = c(1, 2))
ggsave('bubble_heatmep.pdf',width = 10,height = 5)
❝You can adjust it a little bit in AI later~
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