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Initial_screen_meth_groups.R
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setwd("~/Bioinformatics Work/Meth & RNA/Meth_overview")
library(survival)
############# Including normals first
### Load in the normals files for each subset
Fang_200a <- read.table("Fang_TSS200_all_exp_set.txt", sep ="\t", header = TRUE, row.names = 1)
########### create factors
Pam50 <- as.factor(Fang_200a$Pam50)
Quar <- as.factor(Fang_200a$Quartile)
Tert <- as.factor(Fang_200a$Tertile)
boxplot(Fang_200a$DNMT1 ~ Pam50)
boxplot(Fang_200a$DNMT1 ~ Quar)
boxplot(Fang_200a$DNMT1 ~ Tert)
boxplot(Fang_200a$MethScore ~ Pam50)
aov.out = aov(Fang_200a$DNMT3B ~ Pam50)
summary(aov.out)
TukeyHSD(aov.out)
### Survivial curves
fit.diff = survdiff(Surv(Survival_time,Survival_event == 1) ~ factor(Quar),
data=Fang_200a)
chisq2 = signif(1-pchisq(fit.diff$chisq,length(levels(factor(Quar)))-1),3)
fit1 = survfit(Surv(Survival_time,Survival_event == 1)~Quar,
data=Fang_200a,conf.type="log-log")
kmcolours <- c("black", "red", "green", "blue")
plot(fit1, conf.int=F,col=kmcolours,xlab="Time to death (days)",
ylab="Survival",main=c("All subtype survival by\n methylation quartile"),
lwd=4,mark.time=TRUE)
legend("bottomleft",legend=levels(factor(Quar)),
fill = kmcolours, cex = 1)
###do another anova for signifigance
anova(coxph(Surv(Survival_time,Survival_event == 1)~factor(Quar), data = Fang_200a))
####### by tertile
fit.diff = survdiff(Surv(Survival_time,Survival_event == 1) ~ factor(Tert),
data=Fang_200a)
chisq2 = signif(1-pchisq(fit.diff$chisq,length(levels(factor(Tert)))-1),3)
fit1 = survfit(Surv(Survival_time,Survival_event == 1)~Tert,
data=Fang_200a,conf.type="log-log")
kmcolours <- c("black", "red", "green", "blue")
plot(fit1, conf.int=F,col=kmcolours,xlab="Time to death (days)",
ylab="Survival",main=c("All subtype survival by\n methylation Terttile"),
lwd=4,mark.time=TRUE)
legend("bottomleft",legend=levels(factor(Tert)),
fill = kmcolours, cex = 1)
###do another anova for signifigance
anova(coxph(Surv(Survival_time,Survival_event == 1)~factor(Tert), data = Fang_200a))
##########################################################################
Fang_200i <- read.table("Fang_TSS200_island_exp_set.txt", sep ="\t", header = TRUE, row.names = 1)
########### create factors
Pam50 <- as.factor(Fang_200i$Pam50)
Quar <- as.factor(Fang_200i$Quartile)
Tert <- as.factor(Fang_200i$Tertile)
boxplot(Fang_200i$DNMT1 ~ Pam50)
boxplot(Fang_200i$DNMT1 ~ Quar)
boxplot(Fang_200i$DNMT1 ~ Tert)
boxplot(Fang_200i$MethScore ~ Pam50)
aov.out = aov(Fang_200i$DNMT3B ~ Quar)
summary(aov.out)
TukeyHSD(aov.out)
### Survivial curves
fit.diff = survdiff(Surv(Survival_time,Survival_event == 1) ~ factor(Quar),
data=Fang_200i)
chisq2 = signif(1-pchisq(fit.diff$chisq,length(levels(factor(Quar)))-1),3)
fit1 = survfit(Surv(Survival_time,Survival_event == 1)~Quar,
data=Fang_200i,conf.type="log-log")
kmcolours <- c("black", "red", "green", "blue")
plot(fit1, conf.int=F,col=kmcolours,xlab="Time to death (days)",
ylab="Survival",main=c("All subtype survival by\n methylation quartile"),
lwd=4,mark.time=TRUE)
legend("bottomleft",legend=levels(factor(Quar)),
fill = kmcolours, cex = 1)
###do another anova for signifigance
anova(coxph(Surv(Survival_time,Survival_event == 1)~factor(Quar), data = Fang_200i))
####### by tertile
fit.diff = survdiff(Surv(Survival_time,Survival_event == 1) ~ factor(Tert),
data=Fang_200i)
chisq2 = signif(1-pchisq(fit.diff$chisq,length(levels(factor(Tert)))-1),3)
fit1 = survfit(Surv(Survival_time,Survival_event == 1)~Tert,
data=Fang_200i,conf.type="log-log")
kmcolours <- c("black", "red", "green", "blue")
plot(fit1, conf.int=F,col=kmcolours,xlab="Time to death (days)",
ylab="Survival",main=c("All subtype survival by\n methylation Terttile"),
lwd=4,mark.time=TRUE)
legend("bottomleft",legend=levels(factor(Tert)),
fill = kmcolours, cex = 1)
###do another anova for signifigance
anova(coxph(Surv(Survival_time,Survival_event == 1)~factor(Tert), data = Fang_200i))
#################################################################################################
Fang_1500a <- read.table("Fang_TSS1500_all_exp_set.txt", sep ="\t", header = TRUE, row.names = 1)
########### create factors
Pam50 <- as.factor(Fang_1500a$Pam50)
Quar <- as.factor(Fang_1500a$Quartile)
Tert <- as.factor(Fang_1500a$Tertile)
boxplot(Fang_1500a$DNMT1 ~ Pam50)
boxplot(Fang_1500a$DNMT1 ~ Quar)
boxplot(Fang_1500a$DNMT1 ~ Tert)
boxplot(Fang_1500a$MethScore ~ Pam50)
aov.out = aov(Fang_1500a$DNMT3B ~ Quar)
summary(aov.out)
TukeyHSD(aov.out)
### Survivial curves
fit.diff = survdiff(Surv(Survival_time,Survival_event == 1) ~ factor(Quar),
data=Fang_1500a)
chisq2 = signif(1-pchisq(fit.diff$chisq,length(levels(factor(Quar)))-1),3)
fit1 = survfit(Surv(Survival_time,Survival_event == 1)~Quar,
data=Fang_1500a,conf.type="log-log")
kmcolours <- c("black", "red", "green", "blue")
plot(fit1, conf.int=F,col=kmcolours,xlab="Time to death (days)",
ylab="Survival",main=c("All subtype survival by\n methylation quartile"),
lwd=4,mark.time=TRUE)
legend("bottomleft",legend=levels(factor(Quar)),
fill = kmcolours, cex = 1)
###do another anova for signifigance
anova(coxph(Surv(Survival_time,Survival_event == 1)~factor(Quar), data = Fang_1500a))
####### by tertile
fit.diff = survdiff(Surv(Survival_time,Survival_event == 1) ~ factor(Tert),
data=Fang_1500a)
chisq2 = signif(1-pchisq(fit.diff$chisq,length(levels(factor(Tert)))-1),3)
fit1 = survfit(Surv(Survival_time,Survival_event == 1)~Tert,
data=Fang_1500a,conf.type="log-log")
kmcolours <- c("black", "red", "green", "blue")
plot(fit1, conf.int=F,col=kmcolours,xlab="Time to death (days)",
ylab="Survival",main=c("All subtype survival by\n methylation Terttile"),
lwd=4,mark.time=TRUE)
legend("bottomleft",legend=levels(factor(Tert)),
fill = kmcolours, cex = 1)
###do another anova for signifigance
anova(coxph(Surv(Survival_time,Survival_event == 1)~factor(Tert), data = Fang_1500a))
#####################################################
Fang_1500i <- read.table("Fang_TSS1500_island_exp_set.txt", sep ="\t", header = TRUE, row.names = 1)
########### create factors
Pam50 <- as.factor(Fang_1500i$Pam50)
Quar <- as.factor(Fang_1500i$Quartile)
Tert <- as.factor(Fang_1500i$Tertile)
boxplot(Fang_1500i$DNMT1 ~ Pam50)
boxplot(Fang_1500i$DNMT1 ~ Quar)
boxplot(Fang_1500i$DNMT1 ~ Tert)
boxplot(Fang_1500i$MethScore ~ Pam50)
aov.out = aov(Fang_1500i$DNMT3B ~ Tert)
summary(aov.out)
TukeyHSD(aov.out)
### Survivial curves
fit.diff = survdiff(Surv(Survival_time,Survival_event == 1) ~ factor(Quar),
data=Fang_1500i)
chisq2 = signif(1-pchisq(fit.diff$chisq,length(levels(factor(Quar)))-1),3)
fit1 = survfit(Surv(Survival_time,Survival_event == 1)~Quar,
data=Fang_1500i,conf.type="log-log")
kmcolours <- c("black", "red", "green", "blue")
plot(fit1, conf.int=F,col=kmcolours,xlab="Time to death (days)",
ylab="Survival",main=c("All subtype survival by\n methylation quartile"),
lwd=4,mark.time=TRUE)
legend("bottomleft",legend=levels(factor(Quar)),
fill = kmcolours, cex = 1)
###do another anova for signifigance
anova(coxph(Surv(Survival_time,Survival_event == 1)~factor(Quar), data = Fang_1500i))
####### by tertile
fit.diff = survdiff(Surv(Survival_time,Survival_event == 1) ~ factor(Tert),
data=Fang_1500i)
chisq2 = signif(1-pchisq(fit.diff$chisq,length(levels(factor(Tert)))-1),3)
fit1 = survfit(Surv(Survival_time,Survival_event == 1)~Tert,
data=Fang_1500i,conf.type="log-log")
kmcolours <- c("black", "red", "green", "blue")
plot(fit1, conf.int=F,col=kmcolours,xlab="Time to death (days)",
ylab="Survival",main=c("All subtype survival by\n methylation Terttile"),
lwd=4,mark.time=TRUE)
legend("bottomleft",legend=levels(factor(Tert)),
fill = kmcolours, cex = 1)
###do another anova for signifigance
anova(coxph(Surv(Survival_time,Survival_event == 1)~factor(Tert), data = Fang_1500i))
############################################
#### Stir groups
### Load in the normals files for each subset
Stir_200a <- read.table("Stir_TSS200_all_exp_set.txt", sep ="\t", header = TRUE, row.names = 1)
########### create factors
Pam50 <- as.factor(Stir_200a$Pam50)
Quar <- as.factor(Stir_200a$Quartile)
Tert <- as.factor(Stir_200a$Tertile)
boxplot(Stir_200a$DNMT1 ~ Pam50)
boxplot(Stir_200a$DNMT1 ~ Quar)
boxplot(Stir_200a$DNMT1 ~ Tert)
boxplot(Stir_200a$MethScore ~ Pam50)
aov.out = aov(Stir_200a$DNMT1 ~ Quar)
summary(aov.out)
TukeyHSD(aov.out)
### Survivial curves
fit.diff = survdiff(Surv(Survival_time,Survival_event == 1) ~ factor(Quar),
data=Stir_200a)
chisq2 = signif(1-pchisq(fit.diff$chisq,length(levels(factor(Quar)))-1),3)
fit1 = survfit(Surv(Survival_time,Survival_event == 1)~Quar,
data=Stir_200a,conf.type="log-log")
kmcolours <- c("black", "red", "green", "blue")
plot(fit1, conf.int=F,col=kmcolours,xlab="Time to death (days)",
ylab="Survival",main=c("All subtype survival by\n methylation quartile"),
lwd=4,mark.time=TRUE)
legend("bottomleft",legend=levels(factor(Quar)),
fill = kmcolours, cex = 1)
###do another anova for signifigance
anova(coxph(Surv(Survival_time,Survival_event == 1)~factor(Quar), data = Stir_200a))
####### by tertile
fit.diff = survdiff(Surv(Survival_time,Survival_event == 1) ~ factor(Tert),
data=Stir_200a)
chisq2 = signif(1-pchisq(fit.diff$chisq,length(levels(factor(Tert)))-1),3)
fit1 = survfit(Surv(Survival_time,Survival_event == 1)~Tert,
data=Stir_200a,conf.type="log-log")
kmcolours <- c("black", "red", "green", "blue")
plot(fit1, conf.int=F,col=kmcolours,xlab="Time to death (days)",
ylab="Survival",main=c("All subtype survival by\n methylation Terttile"),
lwd=4,mark.time=TRUE)
legend("bottomleft",legend=levels(factor(Tert)),
fill = kmcolours, cex = 1)
###do another anova for signifigance
anova(coxph(Surv(Survival_time,Survival_event == 1)~factor(Tert), data = Stir_200a))
##########################################################################
Stir_200i <- read.table("Stir_TSS200_island_exp_set.txt", sep ="\t", header = TRUE, row.names = 1)
########### create factors
Pam50 <- as.factor(Stir_200i$Pam50)
Quar <- as.factor(Stir_200i$Quartile)
Tert <- as.factor(Stir_200i$Tertile)
boxplot(Stir_200i$DNMT1 ~ Pam50)
boxplot(Stir_200i$DNMT1 ~ Quar)
boxplot(Stir_200i$DNMT1 ~ Tert)
boxplot(Stir_200i$MethScore ~ Pam50)
aov.out = aov(Stir_200i$DNMT1 ~ Quar)
summary(aov.out)
TukeyHSD(aov.out)
### Survivial curves
fit.diff = survdiff(Surv(Survival_time,Survival_event == 1) ~ factor(Quar),
data=Stir_200i)
chisq2 = signif(1-pchisq(fit.diff$chisq,length(levels(factor(Quar)))-1),3)
fit1 = survfit(Surv(Survival_time,Survival_event == 1)~Quar,
data=Stir_200i,conf.type="log-log")
kmcolours <- c("black", "red", "green", "blue")
plot(fit1, conf.int=F,col=kmcolours,xlab="Time to death (days)",
ylab="Survival",main=c("All subtype survival by\n methylation quartile"),
lwd=4,mark.time=TRUE)
legend("bottomleft",legend=levels(factor(Quar)),
fill = kmcolours, cex = 1)
###do another anova for signifigance
anova(coxph(Surv(Survival_time,Survival_event == 1)~factor(Quar), data = Stir_200i))
####### by tertile
fit.diff = survdiff(Surv(Survival_time,Survival_event == 1) ~ factor(Tert),
data=Stir_200i)
chisq2 = signif(1-pchisq(fit.diff$chisq,length(levels(factor(Tert)))-1),3)
fit1 = survfit(Surv(Survival_time,Survival_event == 1)~Tert,
data=Stir_200i,conf.type="log-log")
kmcolours <- c("black", "red", "green", "blue")
plot(fit1, conf.int=F,col=kmcolours,xlab="Time to death (days)",
ylab="Survival",main=c("All subtype survival by\n methylation Terttile"),
lwd=4,mark.time=TRUE)
legend("bottomleft",legend=levels(factor(Tert)),
fill = kmcolours, cex = 1)
###do another anova for signifigance
anova(coxph(Surv(Survival_time,Survival_event == 1)~factor(Tert), data = Stir_200i))
#################################################################################################
Stir_1500a <- read.table("Stir_TSS1500_all_exp_set.txt", sep ="\t", header = TRUE, row.names = 1)
########### create factors
Pam50 <- as.factor(Stir_1500a$Pam50)
Quar <- as.factor(Stir_1500a$Quartile)
Tert <- as.factor(Stir_1500a$Tertile)
boxplot(Stir_1500a$DNMT1 ~ Pam50)
boxplot(Stir_1500a$DNMT1 ~ Quar)
boxplot(Stir_1500a$DNMT1 ~ Tert)
boxplot(Stir_1500a$MethScore ~ Pam50)
aov.out = aov(Stir_1500a$DNMT1 ~ Quar)
summary(aov.out)
TukeyHSD(aov.out)
### Survivial curves
fit.diff = survdiff(Surv(Survival_time,Survival_event == 1) ~ factor(Quar),
data=Stir_1500a)
chisq2 = signif(1-pchisq(fit.diff$chisq,length(levels(factor(Quar)))-1),3)
fit1 = survfit(Surv(Survival_time,Survival_event == 1)~Quar,
data=Stir_1500a,conf.type="log-log")
kmcolours <- c("black", "red", "green", "blue")
plot(fit1, conf.int=F,col=kmcolours,xlab="Time to death (days)",
ylab="Survival",main=c("All subtype survival by\n methylation quartile"),
lwd=4,mark.time=TRUE)
legend("bottomleft",legend=levels(factor(Quar)),
fill = kmcolours, cex = 1)
###do another anova for signifigance
anova(coxph(Surv(Survival_time,Survival_event == 1)~factor(Quar), data = Stir_1500a))
####### by tertile
fit.diff = survdiff(Surv(Survival_time,Survival_event == 1) ~ factor(Tert),
data=Stir_1500a)
chisq2 = signif(1-pchisq(fit.diff$chisq,length(levels(factor(Tert)))-1),3)
fit1 = survfit(Surv(Survival_time,Survival_event == 1)~Tert,
data=Stir_1500a,conf.type="log-log")
kmcolours <- c("black", "red", "green", "blue")
plot(fit1, conf.int=F,col=kmcolours,xlab="Time to death (days)",
ylab="Survival",main=c("All subtype survival by\n methylation Terttile"),
lwd=4,mark.time=TRUE)
legend("bottomleft",legend=levels(factor(Tert)),
fill = kmcolours, cex = 1)
###do another anova for signifigance
anova(coxph(Surv(Survival_time,Survival_event == 1)~factor(Tert), data = Stir_1500a))
#####################################################
Stir_1500i <- read.table("Stir_TSS1500_island_exp_set.txt", sep ="\t", header = TRUE, row.names = 1)
########### create factors
Pam50 <- as.factor(Stir_1500i$Pam50)
Quar <- as.factor(Stir_1500i$Quartile)
Tert <- as.factor(Stir_1500i$Tertile)
boxplot(Stir_1500i$DNMT1 ~ Pam50)
boxplot(Stir_1500i$DNMT1 ~ Quar)
boxplot(Stir_1500i$DNMT1 ~ Tert)
boxplot(Stir_1500i$MethScore ~ Pam50)
aov.out = aov(Stir_1500i$DNMT1 ~ Quar)
summary(aov.out)
TukeyHSD(aov.out)
### Survivial curves
fit.diff = survdiff(Surv(Survival_time,Survival_event == 1) ~ factor(Quar),
data=Stir_1500i)
chisq2 = signif(1-pchisq(fit.diff$chisq,length(levels(factor(Quar)))-1),3)
fit1 = survfit(Surv(Survival_time,Survival_event == 1)~Quar,
data=Stir_1500i,conf.type="log-log")
kmcolours <- c("black", "red", "green", "blue")
plot(fit1, conf.int=F,col=kmcolours,xlab="Time to death (days)",
ylab="Survival",main=c("All subtype survival by\n methylation quartile"),
lwd=4,mark.time=TRUE)
legend("bottomleft",legend=levels(factor(Quar)),
fill = kmcolours, cex = 1)
###do another anova for signifigance
anova(coxph(Surv(Survival_time,Survival_event == 1)~factor(Quar), data = Stir_1500i))
####### by tertile
fit.diff = survdiff(Surv(Survival_time,Survival_event == 1) ~ factor(Tert),
data=Stir_1500i)
chisq2 = signif(1-pchisq(fit.diff$chisq,length(levels(factor(Tert)))-1),3)
fit1 = survfit(Surv(Survival_time,Survival_event == 1)~Tert,
data=Stir_1500i,conf.type="log-log")
kmcolours <- c("black", "red", "green", "blue")
plot(fit1, conf.int=F,col=kmcolours,xlab="Time to death (days)",
ylab="Survival",main=c("All subtype survival by\n methylation Terttile"),
lwd=4,mark.time=TRUE)
legend("bottomleft",legend=levels(factor(Tert)),
fill = kmcolours, cex = 1)
###do another anova for signifigance
anova(coxph(Surv(Survival_time,Survival_event == 1)~factor(Tert), data = Stir_1500i))