当前位置:网站首页>HOW TO ADD P-VALUES TO GGPLOT FACETS
HOW TO ADD P-VALUES TO GGPLOT FACETS
2022-07-02 11:49:00 【Xiaoyu 2022】
library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
stat.test <- df %>%
group_by(dose) %>%
t_test(len ~ supp) %>%
adjust_pvalue(method = "bonferroni") %>%
add_significance()
# Create a box plot
bxp <- ggboxplot(
df, x = "supp", y = "len", fill = "#00AFBB",
facet.by = "dose"
)
# Make facet and add p-values
stat.test <- stat.test %>% add_xy_position(x = "supp")
bxp + stat_pvalue_manual(stat.test)

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
stat.test <- df %>%
group_by(dose) %>%
t_test(len ~ supp) %>%
adjust_pvalue(method = "bonferroni") %>%
add_significance()
# Create a box plot
bxp <- ggboxplot(
df, x = "supp", y = "len", fill = "#00AFBB",
facet.by = "dose"
)
# Make facet and add p-values
stat.test <- stat.test %>% add_xy_position(x = "supp")
bxp + stat_pvalue_manual(stat.test)
# Make the facet scale free and add jitter points
# Move down the bracket using `bracket.nudge.y`
# Hide ns (non-significant)
# Show adjusted p-values and significance levels
# Add 10% spaces between the p-value labels and the plot border
bxp <- ggboxplot(
df, x = "supp", y = "len", fill = "#00AFBB",
facet.by = "dose", scales = "free", add = "jitter"
)
bxp +
stat_pvalue_manual(
stat.test, bracket.nudge.y = -2, hide.ns = TRUE,
label = "{p.adj}{p.adj.signif}"
) +
scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
df, x = "supp", y = "len", add = "mean_sd",
fill = "#00AFBB", facet.by = "dose"
)
# Add p-values onto the bar plots
stat.test <- stat.test %>% add_xy_position(fun = "mean_sd", x = "supp")
bp + stat_pvalue_manual(stat.test)

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
df, x = "supp", y = "len", add = c("mean_sd", "jitter"),
fill = "#00AFBB", facet.by = "dose"
)
# Add p-values onto the bar plots
stat.test <- stat.test %>% add_xy_position(fun = "max", x = "supp")
bp + stat_pvalue_manual(stat.test)

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
df, x = "supp", y = "len", add = c("mean_sd", "jitter"),
fill = "#00AFBB", facet.by = "dose"
)
stat.test <- df %>%
group_by(group, dose) %>%
t_test(len ~ supp) %>%
adjust_pvalue(method = "bonferroni") %>%
add_significance()
# Create box plots with significance levels
# Hide ns (non-significant)
stat.test <- stat.test %>% add_xy_position(x = "supp")
ggboxplot(
df, x = "supp", y = "len", fill = "#E7B800",
facet = c("group", "dose")
) +
stat_pvalue_manual(stat.test, hide.ns = TRUE)

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
df, x = "supp", y = "len", add = c("mean_sd", "jitter"),
fill = "#00AFBB", facet.by = "dose"
)
stat.test <- df %>%
group_by(group, dose) %>%
t_test(len ~ supp) %>%
adjust_pvalue(method = "bonferroni") %>%
add_significance()
# Create bar plots with significance levels
# Hide ns (non-significant)
stat.test <- stat.test %>% add_xy_position(x = "supp", fun = "mean_sd")
ggbarplot(
df, x = "supp", y = "len", fill = "#E7B800",
add = c("mean_sd", "jitter"), facet = c("group", "dose")
) +
stat_pvalue_manual(stat.test, hide.ns = TRUE)

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
df, x = "supp", y = "len", add = c("mean_sd", "jitter"),
fill = "#00AFBB", facet.by = "dose"
)
stat.test <- df %>%
group_by(supp) %>%
t_test(len ~ dose)
# Box plots with p-values
stat.test <- stat.test %>% add_y_position()
ggboxplot(df, x = "dose", y = "len", fill = "#FC4E07", facet.by = "supp") +
stat_pvalue_manual(stat.test, label = "p.adj.signif", tip.length = 0.01) +
scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
df, x = "supp", y = "len", add = c("mean_sd", "jitter"),
fill = "#00AFBB", facet.by = "dose"
)
# Bar plot with p-values
# Add 10% space on the y-axis above the box plots
stat.test <- stat.test %>% add_y_position(fun = "mean_sd")
ggbarplot(
df, x = "dose", y = "len", fill = "#FC4E07",
add = "mean_sd", facet.by = "supp"
) +
stat_pvalue_manual(stat.test, label = "p.adj.signif", tip.length = 0.01) +
scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
df, x = "supp", y = "len", add = c("mean_sd", "jitter"),
fill = "#00AFBB", facet.by = "dose"
)
stat.test <- df %>%
group_by(supp) %>%
t_test(len ~ dose, ref.group = "0.5")
# Box plots with p-values
stat.test <- stat.test %>% add_y_position()
ggboxplot(df, x = "dose", y = "len", fill = "#FC4E07", facet.by = "supp") +
stat_pvalue_manual(stat.test, label = "p.adj.signif", tip.length = 0.01) +
scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
df, x = "supp", y = "len", add = c("mean_sd", "jitter"),
fill = "#00AFBB", facet.by = "dose"
)
# Show only significance levels at x = group2
# Move down significance symbols using vjust
stat.test <- stat.test %>% add_y_position()
ggboxplot(df, x = "dose", y = "len", fill = "#FC4E07", facet.by = "supp") +
stat_pvalue_manual(stat.test, label = "p.adj.signif", x = "group2", vjust = 2)

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
df, x = "supp", y = "len", add = c("mean_sd", "jitter"),
fill = "#00AFBB", facet.by = "dose"
)
# Bar plot with p-values
# Add 10% space on the y-axis above the box plots
stat.test <- stat.test %>% add_y_position(fun = "mean_sd")
ggbarplot(
df, x = "dose", y = "len", fill = "#FC4E07",
add = c("mean_sd", "jitter"), facet.by = "supp"
) +
stat_pvalue_manual(stat.test, label = "p.adj.signif", tip.length = 0.01) +
scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
df, x = "supp", y = "len", add = c("mean_sd", "jitter"),
fill = "#00AFBB", facet.by = "dose"
)
# Create box plots with significance levels
# Hide ns (non-significant)
# Add 15% space between labels and the plot top border
stat.test <- stat.test %>% add_xy_position(x = "dose")
ggboxplot(
df, x = "dose", y = "len", fill = "#FC4E07",
facet = c("group", "supp"),
)
stat_pvalue_manual(stat.test, hide.ns = TRUE)
scale_y_continuous(expand = expansion(mult = c(0.05, 0.15)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
df, x = "supp", y = "len", add = c("mean_sd", "jitter"),
fill = "#00AFBB", facet.by = "dose"
)
# Create bar plots with significance levels
# Hide ns (non-significant)
# Add 15% space between labels and the plot top border
stat.test <- stat.test %>% add_xy_position(x = "dose", fun = "mean_sd")
ggbarplot(
df, x = "dose", y = "len", fill = "#FC4E07",
add = c("mean_sd", "jitter"), facet = c("group", "supp")
)
stat_pvalue_manual(stat.test, hide.ns = TRUE)
scale_y_continuous(expand = expansion(mult = c(0.05, 0.15)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
df, x = "supp", y = "len", add = c("mean_sd", "jitter"),
fill = "#00AFBB", facet.by = "dose"
)
# Box plots
bxp <- ggboxplot(
df, x = "supp", y = "len", color = "dose",
palette = "jco", facet.by = "group"
)
bxp

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
df, x = "supp", y = "len", add = c("mean_sd", "jitter"),
fill = "#00AFBB", facet.by = "dose"
)
# Bar plots
bp <- ggbarplot(
df, x = "supp", y = "len", color = "dose",
palette = "jco", add = "mean_sd",
position = position_dodge(0.8),
facet.by = "group"
)
bp

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
df, x = "supp", y = "len", add = c("mean_sd", "jitter"),
fill = "#00AFBB", facet.by = "dose"
)
stat.test <- df %>%
group_by(supp, group) %>%
t_test(len ~ dose)
# Box plots with p-values
# Hide ns (non-significant)
stat.test <- stat.test %>%
add_xy_position(x = "supp", dodge = 0.8)
bxp +
stat_pvalue_manual(
stat.test, label = "p.adj.signif", tip.length = 0.01,
hide.ns = TRUE
) +
scale_y_continuous(expand = expansion(mult = c(0.01, 0.1)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
df, x = "supp", y = "len", add = c("mean_sd", "jitter"),
fill = "#00AFBB", facet.by = "dose"
)
# Bar plots with p-values
stat.test <- stat.test %>%
add_xy_position(x = "supp", fun = "mean_sd", dodge = 0.8)
bp
stat_pvalue_manual(
stat.test, label = "p.adj.signif", tip.length = 0.01,
hide.ns = TRUE
)
scale_y_continuous(expand = expansion(mult = c(0.01, 0.1)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
df, x = "supp", y = "len", add = c("mean_sd", "jitter"),
fill = "#00AFBB", facet.by = "dose"
)
stat.test <- df %>%
group_by(supp, group) %>%
t_test(len ~ dose, ref.group = "0.5")
stat.test
# Box plots with p-values
stat.test <- stat.test %>%
add_xy_position(x = "supp", dodge = 0.8)
bxp +
stat_pvalue_manual(
stat.test, label = "p.adj.signif", tip.length = 0.01
) +
scale_y_continuous(expand = expansion(mult = c(0.01, 0.1)))

library(ggpubr)
library(rstatix)
# Transform `dose` into factor variable
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
# Create a bar plot with error bars (mean +/- sd)
bp <- ggbarplot(
df, x = "supp", y = "len", add = c("mean_sd", "jitter"),
fill = "#00AFBB", facet.by = "dose"
)
stat.test <- df %>%
group_by(supp, group) %>%
t_test(len ~ dose, ref.group = "0.5")
stat.test
# Bar plots with p-values
stat.test <- stat.test %>%
add_xy_position(x = "supp", fun = "mean_sd", dodge = 0.8)
bp
stat_pvalue_manual(
stat.test, label = "p.adj.signif", tip.length = 0.01
)
scale_y_continuous(expand = expansion(mult = c(0.01, 0.1)))

边栏推荐
- CTF record
- Redis超出最大内存错误OOM command not allowed when used memory &gt; 'maxmemory'
- php 根据经纬度查询距离
- What week is a date obtained by QT
- 行業的分析
- How to Create a Nice Box and Whisker Plot in R
- Some suggestions for young people who are about to enter the workplace in the graduation season
- Eight sorting summaries
- 6方面带你认识LED软膜屏 LED软膜屏尺寸|价格|安装|应用
- How to Create a Nice Box and Whisker Plot in R
猜你喜欢

Three transparent LED displays that were "crowded" in 2022

电脑无缘无故黑屏,无法调节亮度。

Develop scalable contracts based on hardhat and openzeppelin (II)

HOW TO ADD P-VALUES TO GGPLOT FACETS

map集合赋值到数据库

excel表格中选中单元格出现十字带阴影的选中效果

How to Create a Beautiful Plots in R with Summary Statistics Labels

揭露数据不一致的利器 —— 实时核对系统

微信小程序利用百度api达成植物识别

BEAUTIFUL GGPLOT VENN DIAGRAM WITH R
随机推荐
How to Create a Nice Box and Whisker Plot in R
STM32 single chip microcomputer programming learning
JS -- take a number randomly from the array every call, and it cannot be the same as the last time
Always report errors when connecting to MySQL database
PHP query distance according to longitude and latitude
Webauthn - official development document
MySQL basic statement
Order by注入
mysql链表数据存储查询排序问题
CentOS8之mysql基本用法
What is the relationship between digital transformation of manufacturing industry and lean production
Research on and off the Oracle chain
基于Hardhat编写合约测试用例
解决uniapp列表快速滑动页面数据空白问题
GGHIGHLIGHT: EASY WAY TO HIGHLIGHT A GGPLOT IN R
QT meter custom control
deepTools对ChIP-seq数据可视化
to_bytes与from_bytes简单示例
Homer预测motif
GGPlot Examples Best Reference