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grandjeanlab authoredgrandjeanlab authored
README.Rmd 21.85 KiB
title: "TPH2 KO statistics"
output: github_document
author: "Alex Meng, Joanes Grandjean"knitr::opts_chunk$set(echo = TRUE, eval=FALSE,warning = FALSE,message=FALSE)Setup environement
Download DABEST
# you just need to run these once.
install.packages('devtools')
install.pacakges("reshape2")
install.pacakges("wesanderson")
install.packages("svglite")
install.packages("ggpubr")
devtools::install_github("ACCLAB/dabestr")
devtools::install_github("karthik/wesanderson")Load pacakges
library(tidyverse)
library(glue)
library(dabestr)
library(wesanderson) # see https://github.com/karthik/wesanderson
library(reshape2)
library(svglite)
library(ggpubr)
pal <- wes_palette("Darjeeling1")###behavioural tests EPM (Fig1) ##Fig1 dataset description: A. Experimental diagram B. Open arms duration C. Number of entry into closed arms D. Latency time for first time entering open arms E. Total distance moved ##FigS1 dataset description: A. Closed arms duration B. Number of entry into open arms
#Fig1B
df <- read_csv('assets/tables/EPM_open_arms_duration.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2+/-'],var.equal=TRUE)$p.value, t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2+/-','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
Fig1B<-plot(dabest_hedges, palette = pal, rawplot.ylabel = "duration in open arms (%)")
ggsave('assets/figure/Fig1B.svg', plot = Fig1B, device = 'svg',dpi = 300)
Fig1B
dabest_hedges$result %>% mutate(p = p_tmp)
#Fig1C
df <- read_csv('assets/tables/EPM_entry_closed_arms.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2+/-'],var.equal=TRUE)$p.value, t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2+/-','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
Fig1C<-plot(dabest_hedges, palette = pal, rawplot.ylabel = "number of entry")
ggsave('assets/figure/Fig1C.svg', plot = Fig1C, device = 'svg',dpi = 300)
Fig1C
dabest_hedges$result %>% mutate(p = p_tmp)#Fig1D
df <- read_csv('assets/tables/EPM_first_time_entry.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2+/-'],var.equal=TRUE)$p.value, t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2+/-','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
Fig1D<-plot(dabest_hedges, palette = pal, rawplot.ylabel = "latency time (s)")
ggsave('assets/figure/Fig1D.svg', plot = Fig1D, device = 'svg',dpi = 300)
Fig1D
dabest_hedges$result %>% mutate(p = p_tmp)#Fig1E
df <- read_csv('assets/tables/EPM_total_distance.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2+/-'],var.equal=TRUE)$p.value, t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2+/-','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
Fig1E<-plot(dabest_hedges, palette = pal, rawplot.ylabel = "total distance moved (cm)")
ggsave('assets/figure/Fig1E.svg', plot = Fig1E, device = 'svg',dpi = 300)
Fig1E
dabest_hedges$result %>% mutate(p = p_tmp)
Fig1A<-ggplot() + theme_void() #make an empty space for diagram.
ggarrange(ggarrange(Fig1A, Fig1B, ncol = 2, labels = c("A", "B")),
ggarrange(Fig1C, Fig1D, Fig1E, ncol = 3, labels = c("C", "D", "E")),
ncol = 1, nrow = 2, widths = 30, heights=10) #See http://www.sthda.com/english/articles/24-ggpubr-publication-ready-plots/81-ggplot2-easy-way-to-mix-multiple-graphs-on-the-same-page/
#FigS1A
df <- read_csv('assets/tables/EPM_closed_arms_duration.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2+/-'],var.equal=TRUE)$p.value, t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2+/-','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
FigS1A<-plot(dabest_hedges, palette = pal, rawplot.ylabel = "duration in closed arms (%)")
ggsave('assets/figure/FigS1A.svg', plot = FigS1A, device = 'svg',dpi = 300)
FigS1A
dabest_hedges$result %>% mutate(p = p_tmp)#FigS1B
df <- read_csv('assets/tables/EPM_entry_open_arms.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2+/-'],var.equal=TRUE)$p.value, t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2+/-','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
FigS1B<-plot(dabest_hedges, palette = pal, rawplot.ylabel = "number of entry")
ggsave('assets/figure/FigS1B.svg', plot = FigS1B, device = 'svg',dpi = 300)
FigS1B
dabest_hedges$result %>% mutate(p = p_tmp)###behavioural tests Social interaction (Fig2) ##Fig2 dataset description: A. Experimental diagram B. Total no contact C. Total mounting D. Total aggressiveness ##FigS2 dataset description: A. Total no contact at different time intervals B. Total mounting at different time intervals C. Total aggressiveness at different time intervals
#Fig2B
df <- read_csv('assets/tables/SI_total_no_contact.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2+/-'],var.equal=TRUE)$p.value, t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2+/-','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
Fig2B<-plot(dabest_hedges, palette = pal, rawplot.ylabel = "total no contact (%)")
ggsave('assets/figure/Fig2B.svg', plot = Fig2B, device = 'svg',dpi = 300)
Fig2B
dabest_hedges$result %>% mutate(p = p_tmp)#Fig2C
df <- read_csv('assets/tables/SI_total_mounting.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2+/-'],var.equal=TRUE)$p.value, t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2+/-','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
Fig2C<-plot(dabest_hedges, palette = pal, rawplot.ylabel = "total mounting (%)")
ggsave('assets/figure/Fig2C.svg', plot = Fig2C, device = 'svg',dpi = 300)
Fig2C
dabest_hedges$result %>% mutate(p = p_tmp)#Fig2D
df <- read_csv('assets/tables/SI_total_aggressiveness.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2+/-'],var.equal=TRUE)$p.value, t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2+/-','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
Fig2D<-plot(dabest_hedges, palette = pal, rawplot.ylabel = "total aggressiveness (%)")
ggsave('assets/figure/2D.svg', plot = Fig2D, device = 'svg',dpi = 300)
Fig2D
dabest_hedges$result %>% mutate(p = p_tmp)###molecular tests PCR for Oxytocin receptors (Fig3) ##Fig3 dataset description: A: Diagram of brain punching position B. Infralimbic cortex C. Prelimbic cortex D. Paraventricular nucleus E. Dorsal raphe nucleus F. Dorsal granular layer of dentate gyrus G. Ventral CA1 region of hippocampus H. Ventral CA3 region of hippocampus I. Ventral granular layer of dentate gyrus ##FigS3 dataset description A. Central amygdala B. Dorsal CA1 region of hippocampus C. Dorsal CA3 region of hippocampus
#Fig3B
df <- read_csv('assets/tables/PCR_IF.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
plot(dabest_hedges, palette = pal)
Fig3B <- plot(dabest_hedges, palette = pal, rawplot.ylabel = "mRNA level (% vs Tph2+/+)")
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges$result %>% mutate(p = p_tmp)
ggsave('assets/figure/Fig3B.svg', plot = Fig3B, device = 'svg',dpi = 300)#Fig3C
df <- read_csv('assets/tables/PCR_PRL.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
plot(dabest_hedges, palette = pal)
Fig3C <- plot(dabest_hedges, palette = pal, rawplot.ylabel = "mRNA level (% vs Tph2+/+)")
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges$result %>% mutate(p = p_tmp)
ggsave('assets/figure/Fig3C.svg', plot = Fig3C, device = 'svg',dpi = 300)#Fig3D
df <- read_csv('assets/tables/PCR_PVN.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
plot(dabest_hedges, palette = pal)
Fig3D <- plot(dabest_hedges, palette = pal, rawplot.ylabel = "mRNA level (% vs Tph2+/+)")
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges$result %>% mutate(p = p_tmp)
ggsave('assets/figure/Fig3D.svg', plot = Fig3D, device = 'svg',dpi = 300)#Fig3E
df <- read_csv('assets/tables/PCR_DR.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
plot(dabest_hedges, palette = pal)
Fig3E <- plot(dabest_hedges, palette = pal, rawplot.ylabel = "mRNA level (% vs Tph2+/+)")
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges$result %>% mutate(p = p_tmp)
ggsave('assets/figure/Fig3E.svg', plot = Fig3E, device = 'svg',dpi = 300)#Fig3F
df <- read_csv('assets/tables/PCR_dGRDG.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
plot(dabest_hedges, palette = pal)
Fig3F <- plot(dabest_hedges, palette = pal, rawplot.ylabel = "mRNA level (% vs Tph2+/+)")
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges$result %>% mutate(p = p_tmp)
ggsave('assets/figure/Fig3F.svg', plot = Fig3F, device = 'svg',dpi = 300)#Fig3G
df <- read_csv('assets/tables/PCR_vCA1.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
plot(dabest_hedges, palette = pal)
Fig3G <- plot(dabest_hedges, palette = pal, rawplot.ylabel = "mRNA level (% vs Tph2+/+)")
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges$result %>% mutate(p = p_tmp)
ggsave('assets/figure/Fig3G.svg', plot = Fig3G, device = 'svg',dpi = 300)#Fig3H
df <- read_csv('assets/tables/PCR_vCA3.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
plot(dabest_hedges, palette = pal)
Fig3H <- plot(dabest_hedges, palette = pal, rawplot.ylabel = "mRNA level (% vs Tph2+/+)")
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges$result %>% mutate(p = p_tmp)
ggsave('assets/figure/Fig3H.svg', plot = Fig3H, device = 'svg',dpi = 300)#Fig3I
df <- read_csv('assets/tables/PCR_vGRDG.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
plot(dabest_hedges, palette = pal)
Fig3I <- plot(dabest_hedges, palette = pal, rawplot.ylabel = "mRNA level (% vs Tph2+/+)")
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges$result %>% mutate(p = p_tmp)
ggsave('assets/figure/Fig3I.svg', plot = Fig3I, device = 'svg',dpi = 300)#FigS3A
df <- read_csv('assets/tables/PCR_CA.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
plot(dabest_hedges, palette = pal)
FigS3A <- plot(dabest_hedges, palette = pal, rawplot.ylabel = "mRNA level (% vs Tph2+/+)")
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges$result %>% mutate(p = p_tmp)
ggsave('assets/figure/FigS3A.svg', plot = FigS3A, device = 'svg',dpi = 300)#FigS3B
df <- read_csv('assets/tables/PCR_dCA1.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
plot(dabest_hedges, palette = pal)
FigS3B <- plot(dabest_hedges, palette = pal, rawplot.ylabel = "mRNA level (% vs Tph2+/+)")
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges$result %>% mutate(p = p_tmp)
ggsave('assets/figure/FigS3B.svg', plot = FigS3B, device = 'svg',dpi = 300)#FigS3C
df <- read_csv('assets/tables/PCR_dCA3.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
plot(dabest_hedges, palette = pal)
FigS3C <- plot(dabest_hedges, palette = pal, rawplot.ylabel = "mRNA level (% vs Tph2+/+)")
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges$result %>% mutate(p = p_tmp)
ggsave('assets/figure/FigS3C.svg', plot = FigS3C, device = 'svg',dpi = 300)###molecular tests ELISA for Oxytocin (Fig4) ##Fig3 dataset description: A. Diagram of brain punching position B. Medial frontal cortex C. Paraventricular nucleus D. Central amygdala E. Hippocampus
##FigS4 dataset description: A. Dorsal raphe nucleus
#Fig4B
df <- read_csv('assets/tables/OXY_MFC.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
plot(dabest_hedges, palette = pal)
Fig4B <- plot(dabest_hedges, palette = pal, rawplot.ylabel = "pg oxytocin/µg tissue protein/ml")
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges$result %>% mutate(p = p_tmp)
ggsave('assets/figure/Fig4B.svg', plot = Fig4B, device = 'svg',dpi = 300)#Fig4C
df <- read_csv('assets/tables/OXY_PVN.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
plot(dabest_hedges, palette = pal)
Fig4C <- plot(dabest_hedges, palette = pal, rawplot.ylabel = "pg oxytocin/µg tissue protein/ml")
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges$result %>% mutate(p = p_tmp)
ggsave('assets/figure/Fig4C.svg', plot = Fig4C, device = 'svg',dpi = 300)#Fig4D
df <- read_csv('assets/tables/OXY_CA.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
plot(dabest_hedges, palette = pal)
Fig4D <- plot(dabest_hedges, palette = pal, rawplot.ylabel = "pg oxytocin/µg tissue protein/ml")
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges$result %>% mutate(p = p_tmp)
ggsave('assets/figure/Fig4D.svg', plot = Fig4D, device = 'svg',dpi = 300)#Fig4E
df <- read_csv('assets/tables/OXY_HIP.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
plot(dabest_hedges, palette = pal)
Fig4E <- plot(dabest_hedges, palette = pal, rawplot.ylabel = "pg oxytocin/µg tissue protein/ml")
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges$result %>% mutate(p = p_tmp)
ggsave('assets/figure/Fig4E.svg', plot = Fig4E, device = 'svg',dpi = 300)#FigS4A
df <- read_csv('assets/tables/OXY_DR.csv', col_types = cols()) %>% melt() %>% dplyr::rename(group = variable) %>% drop_na()
df %>% group_by(group) %>% summarise(mean=round(mean(value),2), sd=round(sd(value),2))
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2-/-'), paired = FALSE) %>% hedges_g()
dabest_hedges
plot(dabest_hedges, palette = pal)
FigS4A <- plot(dabest_hedges, palette = pal, rawplot.ylabel = "pg oxytocin/µg tissue protein/ml")
p_tmp<- c(t.test(df$value[df$group == 'Tph2+/+'], df$value[df$group == 'Tph2-/-'],var.equal=TRUE)$p.value)
dabest_hedges$result %>% mutate(p = p_tmp)
ggsave('assets/figure/FigS4A.svg', plot = FigS4A, device = 'svg',dpi = 300)what happens if dabest bugs?
#load the table. for other cases, it might help to keep naming consistent between tables, see example. Also, avoid spaces or weird characters in table names.
df <- read_csv('assets/tables/testname_measure.csv', col_types = cols()) %>% melt() %>% rename(group = variable) %>% drop_na()
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2+/-'), paired = FALSE) %>% hedges_g()
#figure will require post-pocessing to make do.
plot(dabest_hedges, palette = pal)
dabest_hedges <- dabest(df, group, value, idx = c('Tph2+/+','Tph2-/-'), paired = FALSE) %>% hedges_g()
#figure will require post-pocessing to make do.
plot(dabest_hedges, palette = pal)
Finally, you can consider https://rpkgs.datanovia.com/ggpubr/reference/ggarrange.html to make composite figures in R. Happy to help you get started.