介绍
- ggplot2绘制分组频率分布直方图和密度图
加载R包
knitr::opts_chunk$set(message = FALSE, warning = FALSE)
library(tidyverse)
library(patchwork)
library(ggpubr)
library(rstatix)
# rm(list = ls())
options(stringsAsFactors = F)
options(future.globals.maxSize = 10000 * 1024^2)
Importing data
inputdata <- data.frame(
GroupA = c(rnorm(80, 4, 2), rnorm(120, 10, 3)),
GroupB = c(rnorm(130, 4, 2), rnorm(70, 10, 3)))
plotdata <- inputdata %>%
tidyr::pivot_longer(
cols = GroupA:GroupB,
names_to = "variable",
values_to = "value")
head(plotdata)
组间检验
stat.test <- plotdata %>%
t_test(value ~ variable) %>%
adjust_pvalue(method = "bonferroni") %>%
add_significance("p.adj")
stat.test
基础图
绘制基础的直方图
p1 <- plotdata %>%
dplyr::filter(variable == "GroupA") %>%
ggplot(aes(x = value)) +
geom_histogram(binwidth = 1, color = "black", fill = "#03B0AB", cex = 1) +
geom_density(aes(value, y = after_stat(count)), color = "black",
fill = "#03B0AB", alpha = 0.2, cex = 1) +
scale_x_continuous(expand = c(0, 0)) +
scale_y_continuous(expand = c(0, 0), limits = c(0, 33)) +
labs(x = NULL, y = "Count") +
theme_classic(base_size = 15) +
theme(axis.text = element_text(color = "black"))
p2 <- plotdata %>%
dplyr::filter(variable == "GroupB") %>%
ggplot(aes(x = value)) +
geom_histogram(binwidth = 1, color = "black", fill = "#FB632E", cex = 1) +
geom_density(aes(value, y = after_stat(count)), color = "black",
fill = "#FB632E", alpha = 0.2, cex = 1) +
scale_x_continuous(expand = c(0, 0)) +
scale_y_continuous(expand = c(0, 0), limits = c(0, 33)) +
labs(x = NULL, y = NULL) +
theme_classic(base_size = 15) +
theme(axis.line.y = element_blank(),
axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.text = element_text(color = "black"))
修图
- 添加显著性结果以及合并图形
pl <- p1 +
geom_rect(aes(xmin = 12,
xmax = 16,
ymin = mean(inputdata$GroupA) + 3 * sd(inputdata$GroupA),
ymax = mean(inputdata$GroupA) + 3.5 * sd(inputdata$GroupA)),
color = "#03B0AB", fill = "transparent", cex = 1) +
annotate("text", x = 13.5 , y = mean(inputdata$GroupA) + 3.2 * sd(inputdata$GroupA),
label = "GroupA", size = 3.5) +
annotate("segment", x = mean(inputdata$GroupA), xend = mean(inputdata$GroupA),
y = 0, yend = 31,
linetype = 2, cex = 1) +
coord_cartesian(clip = "off", xlim = c(ceiling(min(inputdata$GroupA)) - 1,
ceiling(max(inputdata$GroupA)) + 1)) +
theme(axis.title = element_text(size = 11, face = "bold"),
axis.text = element_text(color = "black", size = 9)) +
p2 +
geom_rect(aes(xmin = 12,
xmax = 16,
ymin = mean(inputdata$GroupB) + 3 * sd(inputdata$GroupB),
ymax = mean(inputdata$GroupB) + 3.5 * sd(inputdata$GroupB)),
color = "#FB632E", fill = "transparent", cex = 1) +
annotate("text",x = 13.5, y = mean(inputdata$GroupB) + 3.2 * sd(inputdata$GroupB),
label = "GroupB", size = 3.5) +
annotate("segment", x = mean(inputdata$GroupB), xend = mean(inputdata$GroupB),
y = 0, yend = 31, linetype = 2, cex = 1) +
xlab("Value") +
theme(axis.title.x = element_text(hjust = -0.2)) +
coord_cartesian(clip = "off", xlim = c(ceiling(min(inputdata$GroupB)) - 1,
ceiling(max(inputdata$GroupB)) + 1)) +
annotate("segment", x = -2*mean(inputdata$GroupA), xend = mean(inputdata$GroupB),
y = 31, yend = 31, cex = 1) +
annotate("text", x = -mean(inputdata$GroupA)+2, y = 32, size = 5,
label = paste0("p=", stat.test$p.adj)) +
theme(axis.title = element_text(size = 11, face = "bold"),
axis.text = element_text(color = "black", size = 9))
pl
systemic information
devtools::session_info()
─ Session info ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
setting value
version R version 4.3.3 (2024-02-29)
os macOS Sonoma 14.2
system aarch64, darwin20
ui RStudio
language (EN)
collate en_US.UTF-8
ctype en_US.UTF-8
tz Asia/Shanghai
date 2024-04-24
rstudio 2023.12.1+402 Ocean Storm (desktop)
pandoc 3.1.1 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/ (via rmarkdown)
─ Packages ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
package * version date (UTC) lib source
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backports 1.4.1 2021-12-13 [1] CRAN (R 4.3.0)
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cachem 1.0.8 2023-05-01 [1] CRAN (R 4.3.0)
car 3.1-2 2023-03-30 [1] CRAN (R 4.3.0)
carData 3.0-5 2022-01-06 [1] CRAN (R 4.3.0)
cli 3.6.2 2023-12-11 [1] CRAN (R 4.3.1)
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crayon 1.5.2 2022-09-29 [1] CRAN (R 4.3.0)
devtools 2.4.5 2022-10-11 [1] CRAN (R 4.3.0)
digest 0.6.35 2024-03-11 [1] CRAN (R 4.3.1)
dplyr * 1.1.4 2023-11-17 [1] CRAN (R 4.3.1)
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fansi 1.0.6 2023-12-08 [1] CRAN (R 4.3.1)
farver 2.1.1 2022-07-06 [1] CRAN (R 4.3.0)
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htmlwidgets 1.6.4 2023-12-06 [1] CRAN (R 4.3.1)
httpuv 1.6.15 2024-03-26 [1] CRAN (R 4.3.1)
knitr 1.45 2023-10-30 [1] CRAN (R 4.3.1)
labeling 0.4.3 2023-08-29 [1] CRAN (R 4.3.0)
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magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.3.0)
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pkgbuild 1.4.4 2024-03-17 [1] CRAN (R 4.3.1)
pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.3.0)
pkgload 1.3.4 2024-01-16 [1] CRAN (R 4.3.1)
plyr 1.8.9 2023-10-02 [1] CRAN (R 4.3.1)
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R6 2.5.1 2021-08-19 [1] CRAN (R 4.3.0)
Rcpp 1.0.12 2024-01-09 [1] CRAN (R 4.3.1)
readr * 2.1.5 2024-01-10 [1] CRAN (R 4.3.1)
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scales 1.3.0 2023-11-28 [1] CRAN (R 4.3.1)
sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.3.0)
shiny 1.8.1 2024-03-26 [1] CRAN (R 4.3.1)
stringi 1.8.3 2023-12-11 [1] CRAN (R 4.3.1)
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tidyr * 1.3.1 2024-01-24 [1] CRAN (R 4.3.1)
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[1] /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library
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