13. 富集氣泡圖繪制
清除當(dāng)前環(huán)境中的變量
rm(list=ls())
設(shè)置工作目錄
setwd("C:/Users/Dell/Desktop/R_Plots/13bubble/")
讀取示例數(shù)據(jù)
data <- read.table("demo_bubble.tsv",header = T,
check.names = F,sep="\t")
head(data)
Pathway R0vsR3 All_Unigene Pvalue Qvalue
1 Plant hormone signal transduction 70 254 3.94000e-09 4.33e-07
2 Phenylpropanoid biosynthesis 49 163 5.07000e-08 2.79e-06
3 Phenylalanine metabolism 38 126 1.53000e-06 4.20e-05
4 Plant-pathogen interaction 45 159 1.21000e-06 4.20e-05
5 Flavonoid biosynthesis 11 22 5.86000e-05 1.29e-03
6 Linoleic acid metabolism 11 24 1.58824e-04 2.50e-03
richFactor Pathway ID
1 0.2755906 ko04075
2 0.3006135 ko00940
3 0.3015873 ko00360
4 0.2830189 ko04626
5 0.5000000 ko00941
6 0.4583333 ko00591
基礎(chǔ)symbols函數(shù)繪制氣泡圖
head(mtcars)
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
attach(mtcars)
symbols(wt,mpg,circles=cyl,
inches=0.2,
bg=rainbow(7))
image.png
# 添加文本標(biāo)簽
text(wt,mpg,labels = row.names(mtcars),cex=0.7,pos = 3,offset = 0.8)
image.png
# 將圓圈換成正方形
symbols(wt,mpg,squares=cyl,
inches=0.3,
bg=rainbow(7))
detach(mtcars)
image.png
ggplot2包繪制富集氣泡圖
library(ggplot2)
head(data)
Pathway R0vsR3 All_Unigene Pvalue Qvalue
1 Plant hormone signal transduction 70 254 3.94000e-09 4.33e-07
2 Phenylpropanoid biosynthesis 49 163 5.07000e-08 2.79e-06
3 Phenylalanine metabolism 38 126 1.53000e-06 4.20e-05
4 Plant-pathogen interaction 45 159 1.21000e-06 4.20e-05
5 Flavonoid biosynthesis 11 22 5.86000e-05 1.29e-03
6 Linoleic acid metabolism 11 24 1.58824e-04 2.50e-03
richFactor Pathway ID
1 0.2755906 ko04075
2 0.3006135 ko00940
3 0.3015873 ko00360
4 0.2830189 ko04626
5 0.5000000 ko00941
6 0.4583333 ko00591
# 基礎(chǔ)富集氣泡圖
ggplot(data,aes(x=richFactor,y=Pathway,size=R0vsR3,color=-log10(Qvalue))) + geom_point()
image.png
# 更改顏色进泼，主題，坐標(biāo)軸標(biāo)題
ggplot(data,aes(x=richFactor,y=Pathway,size=R0vsR3,color=-log10(Qvalue))) +
geom_point() + theme_bw() +
scale_colour_gradient(low="green",high="red") +
labs(x="GeneRatio",y="Pathway",title="Top20 enriched pathways",
colour=expression(-log[10]("QValue")),size="Gene number") +
theme(plot.title = element_text(hjust = 0.5))
image.png
ggpubr包繪制富集氣泡圖
library(ggpubr)
data$`-log10(Qvalue)` <- -log10(data$Qvalue)
# 基礎(chǔ)富集氣泡圖
ggscatter(data,x="richFactor",y="Pathway",
size = "R0vsR3",color = "-log10(Qvalue)")
image.png
# 更改顏色，主題夯秃，坐標(biāo)軸標(biāo)題
ggscatter(data,x="richFactor",y="Pathway",
size = "R0vsR3",color = "-log10(Qvalue)",
xlab="GeneRatio",ylab="Pathway",
title="Top20 enriched pathways") +
theme_minimal() +
scale_colour_gradient(low="green",high="red") +
labs(colour=expression(-log[10]("QValue")),size="Gene number") +
theme(plot.title = element_text(hjust = 0.5),legend.position = "right")
image.png
sessionInfo()
R version 3.6.0 (2019-04-26)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18363)
Matrix products: default
locale:
[1] LC_COLLATE=Chinese (Simplified)_China.936
[2] LC_CTYPE=Chinese (Simplified)_China.936
[3] LC_MONETARY=Chinese (Simplified)_China.936
[4] LC_NUMERIC=C
[5] LC_TIME=Chinese (Simplified)_China.936
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] ggpubr_0.2.1 magrittr_1.5 ggplot2_3.2.0
loaded via a namespace (and not attached):
[1] Rcpp_1.0.5 rstudioapi_0.10 knitr_1.23 tidyselect_0.2.5
[5] munsell_0.5.0 colorspace_1.4-1 R6_2.4.0 rlang_0.4.7
[9] dplyr_0.8.3 tools_3.6.0 grid_3.6.0 gtable_0.3.0
[13] xfun_0.8 withr_2.1.2 htmltools_0.3.6 yaml_2.2.0
[17] lazyeval_0.2.2 assertthat_0.2.1 digest_0.6.20 tibble_2.1.3
[21] ggsignif_0.5.0 crayon_1.3.4 purrr_0.3.2 evaluate_0.14
[25] glue_1.3.1 rmarkdown_1.13 labeling_0.3 compiler_3.6.0
[29] pillar_1.4.2 scales_1.0.0 pkgconfig_2.0.2
