MUG data coming from 3 independent Arabidopsis T2 lines.
setwd("~/MUGs")
data <- read.csv("AllMUG.csv", header=T, sep="\t")
data$Rep <- as.factor(data$Rep)
data["Lineall"] <- NA
data <- data[order(data$Line),]
summary(data$Line)
## 347-1 347-10 347-2 347-3 347-4 347-5 347-6 347-7 347-9 391-1
## 3 1 3 2 2 1 2 2 2 3
## 391-10 391-2 391-3 391-4 391-5 391-6 391-7 391-8 391-9 502-1
## 2 3 2 2 2 2 2 2 2 3
## 502-10 502-2 502-3 502-4 502-5 502-6 502-8 502-9 504-1 504-10
## 2 3 3 2 2 1 2 2 3 2
## 504-2 504-3 504-4 504-5 504-6 504-7 504-8 504-9
## 3 2 2 2 1 2 1 2
data$Lineall <-c(rep("347", 18),rep("391", 22), rep("502",20),rep("504",20))
data$Lineall <- as.factor(data$Lineall)
data$Lineall <- factor(data$Lineall, levels = c("504","502","391","347"))
colnames(data) <- c("MU", "Line","Rep","Lineall")
head(data)
## MU Line Rep Lineall
## 5 9.5901 347-1 1 347
## 15 0.4119 347-1 2 347
## 27 2.9407 347-1 3 347
## 69 5.2810 347-10 2 347
## 6 15.2767 347-2 1 347
## 19 7.3616 347-2 2 347
Create boxplots by line and by construct
require(ggplot2)
## Loading required package: ggplot2
p <- ggplot(data, aes(data$Line, data$MU))
q <- ggplot(data, aes(data$Lineall, data$MU))
p + geom_boxplot(aes(fill = data$Lineall)) +
geom_jitter(aes(colour = data$Lineall)) +
theme_classic()+
ylab ("pmol/MU/min/ug protein") +
xlab("Line")
q + geom_boxplot(aes(fill = data$Lineall)) +
theme_classic()+
ylab ("pmol/MU/min/ug protein") +
xlab("Line")
