Error with adding p-values using stat_pvalue_manual into a ggplot
I have a problem with stat_pvalue_manual. They showed an error whenever I ran it with stat_pvalue_manual function. I tried to use stat_compare_means, but it is wrong with p.adj value, so I need to come back with stat_pvalue_manual. Below is my script and data. I hope some one can help me with this issue. Thank you very much!
# Create vectors for each variable
medium <- c(
"MM", "MM", "MM", "MM", "MM", "MM",
"MM", "MM", "MM", "MM", "MM",
"MM", "MM", "MM", "MM", "MM",
"MMGA", "MMGA", "MMGA", "MMGA", "MMGA", "MMGA",
"MMGA", "MMGA", "MMGA", "MMGA", "MMGA"
)
strains <- c(
"A", "A", "A", "A", "A", "A",
"B", "B", "B", "B", "B",
"C", "C", "C", "C", "C",
"A", "A", "A", "A", "A", "A",
"B", "B", "B", "B", "B"
)
value <- c(
0.642396224, 0.642973791, 0.560378425, 0.844780865, 1.202418689, 2.107052006,
0.286002062, 0.207255769, 0.121489854, 0.149735456, 0.292497354,
0.188256332, 0.181433285, 0.407696852, 0.37862504, 0.891960999, 0.465748762,
1.003103112, 1.000750442, 1.001402757, 1.006722153, 0.996919936, 0.991101601,
0.997623183, 0.994042211, 0.999101239, 0.996893329, 1.000764356
)
# Create a dataframe
ggdat <- data.frame(medium, strains, value)
Error:
! Problem while computing aesthetics.
ℹ Error occurred in the 4th layer.
Caused by error in FUN():
! object 'strains' not found
Run rlang::last_trace() to see where the error occurred.
Warning message:
Duplicated aesthetics after name standardisation: size
#####################
library(ggprism)
library(readxl)
library(ggplot2)
library(RColorBrewer)
library(ggpubr)
library(rstatix)
ggdat <- read.csv("ggdat_demo.csv")
#calculate p-val
stat.test <- ggdat %>%
group_by(medium) %>%
t_test(value ~ strains) %>%
adjust_pvalue(method = "bonferroni") %>%
add_significance() %>%
add_xy_position(x = "strains", dodge = 0.8)
#data for mean and sd
df.summary <- ggdat %>% group_by(strains, medium) %>%
summarise(sd = sd(value), value = mean(value)) # generate mean and sd for col plot
ggdat$strains <- factor(ggdat$strains, levels = c("A","B", "C", "D"))
df.summary$strains <- factor(df.summary$strains, levels = c("A","B", "C", "D"))
#graph eror when I add p value
ggplot(ggdat, aes(strains, value, fill=strains)) +
facet_grid(. ~ medium) +
geom_col(data = df.summary, position = position_dodge(0.8), width = 0.7, alpha=1) +
geom_errorbar(data = df.summary, aes(ymin = value-sd, ymax = value+sd),
color="#282828",width = 0.4, position = position_dodge(0.8)) +
geom_point(size=2, position = position_jitterdodge(jitter.width = .5, dodge.width = .8),
cex = 3, alpha=.8, color="#282828", shape=21, stroke = .75) +
# add_pvalue(stat.test, label = "p.adj") +
stat_pvalue_manual(stat.test, label = "p.adj", tip.length = 0) +
theme(legend.text = element_text(size = 12), legend.title = element_text(size = 12),
legend.position = "top",
axis.title.y = element_text(face = "plain", size = 12, color = "black", margin = margin(0,0,0,0,"cm")),
axis.title.x = element_text(face = "plain", size = 12, color = "black", margin = margin(0,0,0,0,"cm")),
axis.text.x = element_text(face = "plain", size = 12, color = "black", angle = 35, vjust = 1, hjust = 1, margin = margin(0,0,0.2,0,"cm")),#
axis.text.y = element_text(face = "plain", size = 12, color = "black", angle = 0, margin = margin(0,0,0,0.2,"cm"))) +
scale_y_continuous(limits = c(0,3), breaks = c(0, 0.5,1, 1.5, 2, 2.5))+
scale_color_manual(name= "Strains",values = c("#E6A226", "#BABBBB", "#21BDC2", "#7AD1ED"),labels=c("A","B", "C", "D")) +
scale_fill_manual(name= "Strains",values = c("#E6A226", "#BABBBB", "#21BDC2", "#7AD1ED"), labels=c("A","B", "C", "D")) +
guides(fill=guide_legend(nrow=1,byrow=TRUE), color=guide_legend(nrow=1, byrow=TRUE))+
theme_bw()
Solution
There's a few issues to address, but the biggest issue (as far as I can tell) is using 'global' aes() with different data sources. If you specify aesthetics separately for each geometry you get an output, e.g.
library(tidyverse)
library(RColorBrewer)
library(ggpubr)
library(rstatix)
#>
#> Attaching package: 'rstatix'
#> The following object is masked from 'package:stats':
#>
#> filter
# Create vectors for each variable
medium <- c(
"MM", "MM", "MM", "MM", "MM", "MM",
"MM", "MM", "MM", "MM", "MM",
"MM", "MM", "MM", "MM", "MM",
"MMGA", "MMGA", "MMGA", "MMGA", "MMGA", "MMGA",
"MMGA", "MMGA", "MMGA", "MMGA", "MMGA"
)
strains <- c(
"A", "A", "A", "A", "A", "A",
"B", "B", "B", "B", "B",
"C", "C", "C", "C", "C",
"A", "A", "A", "A", "A", "A",
"B", "B", "B", "B", "B"
)
value <- c(
0.642396224, 0.642973791, 0.560378425, 0.844780865, 1.202418689, 2.107052006,
0.286002062, 0.207255769, 0.121489854, 0.149735456, 0.292497354,
0.188256332, 0.181433285, 0.407696852, 0.37862504, 0.891960999, 0.465748762,
1.003103112, 1.000750442, 1.001402757, 1.006722153, 0.996919936, 0.991101601,
0.997623183, 0.994042211, 0.999101239, 0.996893329
)
# Create a dataframe
ggdat <- data.frame(medium, strains, value)
#calculate p-val
stat.test <- ggdat %>%
group_by(medium) %>%
t_test(value ~ strains) %>%
adjust_pvalue(method = "bonferroni") %>%
add_significance() %>%
add_xy_position(x = "strains", dodge = 0.8)
#data for mean and sd
df.summary <- ggdat %>% group_by(strains, medium) %>%
summarise(sd = sd(value), value = mean(value)) # generate mean and sd for col plot
#> `summarise()` has grouped output by 'strains'. You can override using the
#> `.groups` argument.
ggdat$strains <- factor(ggdat$strains, levels = c("A","B", "C", "D"))
df.summary$strains <- factor(df.summary$strains, levels = c("A","B", "C", "D"))
df.summary <- ungroup(df.summary)
#graph eror when I add p value
ggplot(ggdat) +
facet_grid(. ~ medium) +
geom_col(data = df.summary, aes(strains, value, fill=strains),
position = position_dodge(0.8), width = 0.7, alpha=1) +
geom_errorbar(data = df.summary, aes(x = strains,
y = value,
ymin = value-sd, ymax = value+sd),
color="#282828",width = 0.4, position = position_dodge(0.8)) +
geom_point(aes(strains, value, fill=strains),
size=2, position = position_jitterdodge(jitter.width = .5, dodge.width = .8),
cex = 3, alpha=.8, color="#282828", shape=21, stroke = .75) +
# add_pvalue(stat.test, label = "p.adj") +
stat_pvalue_manual(stat.test, label = "p.adj", tip.length = 0) +
theme(legend.text = element_text(size = 12), legend.title = element_text(size = 12),
legend.position = "top",
axis.title.y = element_text(face = "plain", size = 12, color = "black", margin = margin(0,0,0,0,"cm")),
axis.title.x = element_text(face = "plain", size = 12, color = "black", margin = margin(0,0,0,0,"cm")),
axis.text.x = element_text(face = "plain", size = 12, color = "black", angle = 35, vjust = 1, hjust = 1, margin = margin(0,0,0.2,0,"cm")),#
axis.text.y = element_text(face = "plain", size = 12, color = "black", angle = 0, margin = margin(0,0,0,0.2,"cm"))) +
scale_y_continuous(limits = c(0,3), breaks = c(0, 0.5,1, 1.5, 2, 2.5))+
scale_color_manual(name= "Strains",values = c("#E6A226", "#BABBBB", "#21BDC2", "#7AD1ED"),labels=c("A","B", "C", "D")) +
scale_fill_manual(name= "Strains",values = c("#E6A226", "#BABBBB", "#21BDC2", "#7AD1ED"), labels=c("A","B", "C", "D")) +
guides(fill=guide_legend(nrow=1,byrow=TRUE), color=guide_legend(nrow=1, byrow=TRUE))+
theme_bw()
#> Warning: Duplicated aesthetics after name standardisation: size
Created on 2023-09-21 with reprex v2.0.2
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