跟着Plos Biology学作图：R语言ggplot2双Y轴折线图
论文Large variation in the association between seasonal antibiotic use and resistance across multiple bacterial species and antibiotic classes
数据代码链接
https://github.com/orgs/gradlab/repositories
今天的推文重复一下论文中的 Figure S3,双Y轴的折线图
经过论文提供的代码运行，得到作图数据集
[*]regressions
[*]ci
https://upload-images.jianshu.io/upload_images/6857799-6aad5885e67728c8.png
[*]dat01$deviates_table[]
将这三个数据集保存为csv文件
library(tidyverse)library(readr)regressions %>% write_csv(file = "regressions.csv")ci %>% write_csv(file = "ci.csv")dat01$deviates_table[] %>% write_csv(file = "deviates_table.csv")作图第一步读取数据集
regressions<-read_csv("regressions.csv")head(regressions)ci<-read_csv("ci.csv")head(ci)deviates_table<-read_csv("deviates_table.csv")head(deviates_table)作图代码
library(ggplot2)col<-"#359023"title<-"Ampicillin *"ratio<-27.79891ggplot()+geom_point(data=deviates_table, aes(x=month,y=seasonal_deviate))+geom_errorbar(data = deviates_table, aes(x = month, ymin = seasonal_deviate - sem, ymax = seasonal_deviate + sem), width = 0.5, color = col)+geom_line(data=regressions, aes(x = month, y = value, color = leg, linetype = leg), size = 0.7) +geom_ribbon(data = ci, aes(x = month, ymin = r_lower, ymax = r_upper), fill = col, alpha = 0.3) +geom_ribbon(data = ci, aes(x = month, ymin = u_upper/ratio, ymax = u_lower/ratio), fill = "grey20", alpha = 0.3) +scale_color_manual(values = c(col, "grey20")) +scale_y_continuous(sec.axis = sec_axis(~. * ratio), limits = c(-.165, .165)) +scale_x_continuous(breaks=c(1, 3, 5, 7, 9, 11)) +ggtitle(title) +xlab("Month") +theme_classic() +guides(color = guide_legend(nrow = 2, byrow = TRUE)) +theme(legend.position = "bottom", legend.title = element_blank(), legend.text = element_text(size = 9), plot.title = element_text(size = 11, hjust = 0.5, face = "bold"), axis.text = element_text(size = 10), axis.title.y = element_blank()) -> f3splotprint(f3splot)添加两个坐标轴的标题
library(ggpubr)f3splot %>% annotate_figure(left = text_grob(expression("Seasonal deviates in resistance ("*log["2"]*"(MIC))"), size = 10, rot = 90)) %>%annotate_figure(right = text_grob("Seasonal deviates in use\n(mean daily claims/10,000 people)", size = 10, rot = 270))https://upload-images.jianshu.io/upload_images/6857799-c6b3d7c1f3729730.png今天推文的示例数据和代码可以在公众号后台留言20220413获取
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