ggplot2 左右两个y轴

2024-03-16 20:48

文章标签 ggplot2 左右两个

本文主要是介绍ggplot2 左右两个y轴，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

z两个ggplot 图合并到一起，一个x轴两个y轴

raw_data <- read_delim('./data/GO_pathway.txt', delim = '\t')
head(raw_data)
library(dplyr)
library(Cairo)double_y_axis <- function(p1, p2){g1 <- ggplot_gtable(ggplot_build(p1))g2 <- ggplot_gtable(ggplot_build(p2))# overlap the panel of 2nd plot on that of 1st plotpp <- c(subset(g1$layout, name == "panel", se = t:r))g <- gtable_add_grob(g1, g2$grobs[[which(g2$layout$name == "panel")]], pp$t, pp$l, pp$b, pp$l)# axis tweaksia <- which(g2$layout$name == "axis-l")ga <- g2$grobs[[ia]]ax <- ga$children[[2]]ax$widths <- rev(ax$widths)ax$grobs <- rev(ax$grobs)ax$grobs[[1]]$x <- ax$grobs[[1]]$x - unit(1, "npc") + unit(0.15, "cm")g <- gtable_add_cols(g, g2$widths[g2$layout[ia, ]$l], length(g$widths) - 1)g <- gtable_add_grob(g, ax, pp$t, length(g$widths) - 1, pp$b)# draw itgrid.draw(g)return(g)
}split_fun <- function(x){tmp_split <- strsplit(x, '~')do.call('rbind', tmp_split)[,2]
}
go_data <- raw_data %>%dplyr::filter(grepl('GO',Term) & PValue<0.01) %>%select(c(1,2,3,5)) %>%dplyr::mutate(term = split_fun(Term)) %>%arrange(Category, PValue)
go_data$term <- factor(go_data$term, levels = unique(go_data$term))# ggplot
library(ggplot2)
library(gtable)
library(grid)grid.newpage()# two plots
p1 <- ggplot(go_data)+geom_bar(aes(x = term, y=Count,  fill=Category), stat = 'identity') +
#   geom_line(aes(term, y=PValue, group=1), stat = 'identity', colour="#B00A13") +
#   geom_point(aes(term, y=PValue, group=1),colour="red", size=3, alpha=0.4)+theme_bw() +scale_fill_manual(values = c('#6f359d', '#F28C42'),labels=c('Biological Process', 'Cellular Component'))+theme(axis.text.x = element_text(angle = 40, hjust=1, vjust=1),axis.ticks.x = element_blank(),legend.position='left'# axis.title.y=element_text(vjust=8))+scale_y_continuous(expand = c(0,0), limits=c(0, 30))+xlab('Go Items')+ylab('The number of genes')# coord_fixed(ratio = 0.6)# 控制长宽比
p1p1 <- p1+coord_fixed(ratio = 0.6)# 控制长宽比p2 <- ggplot(go_data, aes(term, PValue, group=1)) +geom_line( stat = 'identity', colour="#B00A13") +geom_point(colour="red", size=3, alpha=0.4)+scale_y_continuous(limits = c(0, 0.02))+# scale_y_reverse()+scale_x_discrete(breaks=NULL)+theme(axis.text.x = element_text(),axis.ticks.x= element_blank(),# panel.background = element_rect(fill = NA),# panel.grid = element_blank(),legend.position='top')+ylab('')+xlab('')
p2# extract gtable
g <- double_y_axis(p1,p2)tiff("Plot600.tiff", type="cairo", width = 14, height = 8, units = 'in', res = 300)
grid.draw(g)
dev.off()# 在右下角的框里调试好图片, 然后采用
# par('din') 获取宽高
CairoPNG('plotCairo.png', width = 13.58, height = 8.2, units='in', dpi=700)grid.draw(g)
dev.off()