tidyplots for R plotting

用于 R 绘图的 tidyplots

Plot
Author

Jie Hua

Published

May 6, 2025

Modified

May 6, 2025

基本信息 / Basic Information

我注意到 Jan Broder Engler 开发了一个名为 “tidyplots” 的新 R 包。这个包可以用简单的命令生成可直接发表的图，在很大程度上简化了 R 的绘图流程。

I noticed a new R package called “tidyplots” produced by Jan Broder Engler. This package could generate publication ready plots with simple commands, which largely simplified the R plotting process.

手册：https://jbengler.github.io/tidyplots/

The manual: https://jbengler.github.io/tidyplots/

我试用了一下，效果非常好。希望以后会有更多实用的函数。

I had a try and it works very well. I hope there will be more useful functions.

它基于 ggplot2 体系，因此也很容易按我们的需要添加更多特性。

It is based on ggplot2 system, it is also very easy to add more features as we want.

安装 / Installation

Code 
pak::pkg_install("tidyplots")

开发版本可以通过以下方式安装

The development version could be installed with

Code 
pak::pkg_install("jbengler/tidyplots")

绘图 / Plotting

Code 
library(tidyplots)

条形图 / Barplot

First 6 rows of the demo dataframe ‘study’
treatment group dose participant age sex score
A placebo high p01 23 female 2
A placebo high p02 45 male 4
A placebo high p03 32 female 5
A placebo high p04 37 male 4
A placebo high p05 24 female 6
B placebo low p06 23 female 9
Code 
blog_tidyplots_theme(
  study |> 
    tidyplot(x = treatment, y = score, color = treatment) |> 
    add_data_points() |> 
    add_mean_bar(alpha = 0.4) |> 
    add_sem_errorbar() |> 
    adjust_colors(new_colors = colors_discrete_seaside)
)

Barplot

Barplot

堆叠条形图 / Barstack plot

Code 
blog_tidyplots_theme(
  energy |> 
    tidyplot(x = year, y = energy, color = energy_source) |> 
    add_barstack_absolute()
)

它提供了许多实用的绘图函数类型，最好还是到它的官方网站了解如何使用这个包。

It provided many useful types of plotting function, it is better to go to its official website to learn how to use this package.

其他示例 / Other example

Code 
energy |> 
  dplyr::filter(year %in% c(2005, 2010, 2015, 2020)) |> 
  tidyplot(y = energy, color = energy_source) |> 
  add_donut() |> 
  adjust_size(width = 25, height = 25) |>
  adjust_theme_details(
    panel.background = element_rect(fill = "transparent", color = NA),
    plot.background = element_rect(fill = "transparent", color = NA),
    legend.background = element_rect(fill = "transparent", color = NA),
    legend.key = element_rect(fill = "transparent", color = NA),
    strip.background = element_rect(fill = "transparent", color = NA),
    panel.grid = element_blank(),
    panel.border = element_rect(color = "black", fill = NA, linewidth = 0.3),
    axis.ticks = element_line(colour = "black", linewidth = 0.3)
  ) |>
  split_plot(by = year)

Code 
library(tidyverse)
#library(tidyplots)

df <- 
  read_csv("https://tidyplots.org/data/correlation-matrix.csv")

blog_tidyplots_theme(
  df |> 
    tidyplot(x = x, y = y, color = correlation) |> 
    add_heatmap() |> 
    sort_x_axis_labels(order_x) |> 
    sort_y_axis_labels(order_y) |> 
    remove_x_axis() |> 
    remove_y_axis() |> 
    remove_legend_title() |> 
    adjust_legend_position("right") |> 
    adjust_colors(colors_continuous_inferno) |> 
    adjust_theme_details(legend.key.height = unit(1, "null")) |> 
    add_caption("Data source: Spellman PT, et al. 1998. Mol Biol Cell 9(12): 3273-97.")
)

如果 tidyplots 能直接读取 .mcool 或 .hic 文件，那将会非常有帮助。

If tidyplots could directly read .mcool or .hic files, it will be very helpful.

我猜测这正是作者计划要做的事情；我们也可以用其他 R 包把 contact matrix 文件读入 data frame 试一试，但这需要付出更多努力。

I guess it is what he plans to do, we can use other R packages to read the contact matrix files into a dataframe to have a try, but it will take more efforts.