install.packages("Rmisc") install.packages("ggplot2") install.packages("ggpubr") install.packages("reshape") install.packages('ggplot2', repos='http://cran.us.r-project.org') install.packages("ggpubr") if(!require(devtools)) install.packages("devtools") devtools::install_github("kassambara/ggpubr") install.packages("png")
library(Rmisc) library(ggplot2) library(ggpubr) library(reshape) library(png) library(magrittr)
setwd("/Volumes/TITANIUM/qPCR:Spotty paper/RIA/RIA_Spotty_Decitabine_2017") data <- read.csv("RIA_Spotty_Cortisol_2017_by_treatment_grouped_controls.csv",sep = ",")
head(data) str(data) dim(data)
melted <- melt(data, id="Stage") head(melted) summary_data <- summarySE(melted, measurevar="value", Stagevars=c("Stage")) help("summarySE") summary_data
head(data) data_log <- data data_log$E2 <- log(data_log$E2)
head(data_log)
melted_log <- melt(data_log, id="Stage") summary_data_log <- summarySE(melted_log, measurevar="value", Stagevars=c("Stage")) help("summarySE") summary_data_log
hist(log(data$E2))
kruskal.test(E2 ~ Stage, data = data_log) ?kruskal.test
install.packages("PMCMRplus") install.packages("FSA") install.packages("dunn.test")
library(dunn.test) library(FSA)
require(PMCMR) data(data_log2) attach(data_log)
dunnTest(E2~Stage, data=data_log, method="bh")
library(Rmisc) library(ggplot2) library(ggpubr) library(reshape) library(png) library(magrittr)
data <- read.csv("amh.csv",sep = ",")
head(data) str(data) dim(data)
melted <- melt(data, id="Treatment") head(melted) summary_data <- summarySE(melted, measurevar="value", groupvars=c("Treatment")) help("summarySE") summary_data
head(data) data_log2 <- data data_log2$amh <- log2(data_log2$amh)
head(data_log2)
melted_log2 <- melt(data_log2, id="Treatment") summary_data_log2 <- summarySE(melted_log2, measurevar="value", groupvars=c("Treatment"))
to check if by logarithmically transforming our data, the standard deviations grew closer to each other help("summarySE") summary_data_log2
hist(log2(data$amh))
p <- ggboxplot(data_log2, x = "Treatment", y = "amh", palette = c("#000000", "#000000", "#000000"), color = "Treatment", ylab = expression(paste("Relative normalised ", italic("amh"), " expression")), add = "jitter", order = c("CF", "TF", "TP"), ylim = c(0,15))+ theme (panel.background = element_rect(fill = 'white', colour = 'white'))+ theme (axis.line.x = element_line(colour = 'black'))+ theme (axis.line.y = element_line(colour = 'black'))+ theme (axis.text.x = element_text(angle=45, hjust=1))+ theme(legend.position = "none")+ scale_x_discrete(limits=c ("CF", "TF", "TP"), name="Treatment\n") p
pdf (file="amh.pdf", width=5, height=4.25) p dev.off()
kruskal.test(amh ~ Treatment, data = data_log2) ?kruskal.test
install.packages("PMCMRplus") install.packages("FSA") install.packages("dunn.test")
library(dunn.test) library(FSA)
require(PMCMR) data(data_log2) attach(data_log2)
dunnTest(amh~Treatment, data=data_log2, method="bh")