se <- function(x) sqrt(var(x)/(length(x) - 1)) data <- read.csv("/Users/acg/Documents/PhD/Research/Nvs2N Rate Adapt/dryad/dataall.csv", header=T) #ypd dypd<-subset(data, Enviro=="ypd") for (p in dypd$Time){ nam <- paste("dypd",p,sep=".") assign(nam, subset(dypd, Time==p))} for (i in dypd.0$Line){ name <- paste("dypd.0",i,sep=".") dypd.0.i <- assign(name, subset(dypd.0, Line==i)) } dypd.0.N <- subset(dypd.0, Ploidy==1) dypd.0.2N <- subset(dypd.0, Ploidy==2) for (i in dypd.0.N$Rep){ name <- paste("dypd.0.N",i,sep=".") dypd.0.N.i <- assign(name, subset(dypd.0.N, Line==i)) } dypd.0.N.5 <- subset(dypd.0.N, Line==5) for (i in dypd.0.2N$Rep){ name <- paste("dypd.0.2N",i,sep=".") dypd.0.2N.i <- assign(name, subset(dypd.0.2N, Line==i)) } dypd.0.2N.5 <- subset(dypd.0.2N, Line==5) dypd.2.N <- subset(dypd.2, Ploidy==1) dypd.2.2N <- subset(dypd.2, Ploidy==2) for (i in dypd.2.N$Line){ name <- paste("dypd.2.N",i,sep=".") dypd.2.N.i <- assign(name, subset(dypd.2.N, Line==i)) } for (i in dypd.2.2N$Line){ name <- paste("dypd.2.2N",i,sep=".") dypd.2.2N.i <- assign(name, subset(dypd.2.2N, Line==i)) } eqn <- function(p0,sss,Day) ((p0*exp(sss*Day))/(1-p0+p0*exp(sss*Day))) p0s<-c() ssses<-c() namess<-c() dataset<-dypd.0.N.1 funcnls<-function(dataset){ huh<-nls(DATA~eqn(p0,sss,Day), data=dataset, start=list(p0=0.4,sss=0.1))} dypd.0.N.1.par <- funcnls(dypd.0.N.1) dypd.0.N.2.par <- funcnls(dypd.0.N.2) dypd.0.N.3.par <- funcnls(dypd.0.N.3) #dypd.0.N.4.par <- funcnls(dypd.0.N.4) dypd.0.N.5.par <- funcnls(dypd.0.N.5) dypd.0.2N.1.par <- funcnls(dypd.0.2N.1) dypd.0.2N.2.par <- funcnls(dypd.0.2N.2) dypd.0.2N.3.par <- funcnls(dypd.0.2N.3) dypd.0.2N.4.par <- funcnls(dypd.0.2N.4) dypd.0.2N.5.par <- funcnls(dypd.0.2N.5) dypd.2.N.1.par <- funcnls(dypd.2.N.1) dypd.2.N.2.par <- funcnls(dypd.2.N.2) dypd.2.N.3.par <- funcnls(dypd.2.N.3) dypd.2.N.4.par <- funcnls(dypd.2.N.4) dypd.2.N.5.par <- funcnls(dypd.2.N.5) dypd.2.2N.1.par <- funcnls(dypd.2.2N.1) dypd.2.2N.2.par <- funcnls(dypd.2.2N.2) dypd.2.2N.3.par <- funcnls(dypd.2.2N.3) dypd.2.2N.4.par <- funcnls(dypd.2.2N.4) dypd.2.2N.5.par <- funcnls(dypd.2.2N.5) time <-c(0,2) ypd.1.1 <- cbind(c(49,189), c(coef(dypd.0.N.1.par)[2],coef(dypd.2.N.1.par)[2])) ypd.1.2 <- cbind(c(49,189), c(coef(dypd.0.N.2.par)[2],coef(dypd.2.N.2.par)[2])) ypd.1.3 <- cbind(c(49,189), c(coef(dypd.0.N.3.par)[2],coef(dypd.2.N.3.par)[2])) ypd.1.5 <- cbind(c(49,189), c(coef(dypd.0.N.5.par)[2],coef(dypd.2.N.5.par)[2])) ypd.2.1 <- cbind(c(49,189), c(coef(dypd.0.2N.1.par)[2],coef(dypd.2.2N.1.par)[2])) ypd.2.2 <- cbind(c(49,189), c(coef(dypd.0.2N.2.par)[2],coef(dypd.2.2N.2.par)[2])) ypd.2.3 <- cbind(c(49,189), c(coef(dypd.0.2N.3.par)[2],coef(dypd.2.2N.3.par)[2])) ypd.2.4 <- cbind(c(49,189), c(coef(dypd.0.2N.4.par)[2],coef(dypd.2.2N.4.par)[2])) ypd.2.5 <- cbind(c(49,189), c(coef(dypd.0.2N.5.par)[2],coef(dypd.2.2N.5.par)[2])) lm.ypd.1.1 <- lm(ypd.1.1[,2]~ypd.1.1[,1]) lm.ypd.1.2 <- lm(ypd.1.2[,2]~ypd.1.2[,1]) lm.ypd.1.3 <- lm(ypd.1.3[,2]~ypd.1.3[,1]) lm.ypd.1.5 <- lm(ypd.1.5[,2]~ypd.1.5[,1]) lm.ypd.2.1 <- lm(ypd.2.1[,2]~ypd.2.1[,1]) lm.ypd.2.2 <- lm(ypd.2.2[,2]~ypd.2.2[,1]) lm.ypd.2.3 <- lm(ypd.2.3[,2]~ypd.2.3[,1]) lm.ypd.2.4 <- lm(ypd.2.4[,2]~ypd.2.4[,1]) lm.ypd.2.5 <- lm(ypd.2.5[,2]~ypd.2.5[,1]) lm.ypd.1 <- c(lm.ypd.1.1$coefficients[2],lm.ypd.1.2$coefficients[2] /6.7,lm.ypd.1.3$coefficients[2]/6.7,lm.ypd.1.5$coefficients[2] /6.7 ) lm.ypd.2 <- c(lm.ypd.2.1$coefficients[2] /6.7,lm.ypd.2.2$coefficients[2] /6.7,lm.ypd.2.3$coefficients[2] /6.7,lm.ypd.2.4$coefficients[2] /6.7,lm.ypd.2.5$coefficients[2] /6.7 ) lm.ypd.1.ave <- mean(lm.ypd.1) lm.ypd.1.se <- se(lm.ypd.1) lm.ypd.2.ave <- mean(lm.ypd.2) lm.ypd.2.se <- se(lm.ypd.2) ypd.ttest2 <- t.test(lm.ypd.1, lm.ypd.2) ypd.ttest2 #nac dnac<-subset(data, Enviro=="nac") for (p in dnac$Time){ nam <- paste("dnac",p,sep=".") assign(nam, subset(dnac, Time==p))} for (i in dnac.0$Line){ name <- paste("dnac.0",i,sep=".") dnac.0.i <- assign(name, subset(dnac.0, Line==i)) } dnac.0.N <- subset(dnac.0, Ploidy==1) dnac.0.2N <- subset(dnac.0, Ploidy==2) for (i in dnac.0.N$Rep){ name <- paste("dnac.0.N",i,sep=".") dnac.0.N.i <- assign(name, subset(dnac.0.N, Line==i)) } dnac.0.N.5 <- subset(dnac.0.N, Line==5) for (i in dnac.0.2N$Rep){ name <- paste("dnac.0.2N",i,sep=".") dnac.0.2N.i <- assign(name, subset(dnac.0.2N, Line==i)) } dnac.0.2N.5 <- subset(dnac.0.2N, Line==5) dnac.2.N <- subset(dnac.2, Ploidy==1) dnac.2.2N <- subset(dnac.2, Ploidy==2) for (i in dnac.2.N$Line){ name <- paste("dnac.2.N",i,sep=".") dnac.2.N.i <- assign(name, subset(dnac.2.N, Line==i)) } for (i in dnac.2.2N$Line){ name <- paste("dnac.2.2N",i,sep=".") dnac.2.2N.i <- assign(name, subset(dnac.2.2N, Line==i)) } eqn <- function(p0,sss,Day) ((p0*exp(sss*Day))/(1-p0+p0*exp(sss*Day))) p0s<-c() ssses<-c() namess<-c() dataset<-dnac.0.N.1 funcnls<-function(dataset){ huh<-nls(DATA~eqn(p0,sss,Day), data=dataset, start=list(p0=0.4,sss=0.1))} dnac.0.N.1.par <- funcnls(dnac.0.N.1) dnac.0.N.2.par <- funcnls(dnac.0.N.2) dnac.0.N.3.par <- funcnls(dnac.0.N.3) dnac.0.N.4.par <- funcnls(dnac.0.N.4) dnac.0.N.5.par <- funcnls(dnac.0.N.5) dnac.0.2N.1.par <- funcnls(dnac.0.2N.1) dnac.0.2N.2.par <- funcnls(dnac.0.2N.2) dnac.0.2N.3.par <- funcnls(dnac.0.2N.3) dnac.0.2N.4.par <- funcnls(dnac.0.2N.4) dnac.0.2N.5.par <- funcnls(dnac.0.2N.5) dnac.2.N.1.par <- funcnls(dnac.2.N.1) dnac.2.N.2.par <- funcnls(dnac.2.N.2) dnac.2.N.3.par <- funcnls(dnac.2.N.3) dnac.2.N.4.par <- funcnls(dnac.2.N.4) dnac.2.N.5.par <- funcnls(dnac.2.N.5) dnac.2.2N.1.par <- funcnls(dnac.2.2N.1) dnac.2.2N.2.par <- funcnls(dnac.2.2N.2) dnac.2.2N.3.par <- funcnls(dnac.2.2N.3) dnac.2.2N.4.par <- funcnls(dnac.2.2N.4) dnac.2.2N.5.par <- funcnls(dnac.2.2N.5) nac.1.1 <- cbind(c(49,189), c(coef(dnac.0.N.1.par)[2],coef(dnac.2.N.1.par)[2])) nac.1.2 <- cbind(c(49,189), c(coef(dnac.0.N.2.par)[2],coef(dnac.2.N.2.par)[2])) nac.1.3 <- cbind(c(49,189), c(coef(dnac.0.N.3.par)[2],coef(dnac.2.N.3.par)[2])) nac.1.4 <- cbind(c(49,189), c(coef(dnac.0.N.4.par)[2],coef(dnac.2.N.4.par)[2])) nac.1.5 <- cbind(c(49,189), c(coef(dnac.0.N.5.par)[2],coef(dnac.2.N.5.par)[2])) nac.2.1 <- cbind(c(49,189), c(coef(dnac.0.2N.1.par)[2],coef(dnac.2.2N.1.par)[2])) nac.2.2 <- cbind(c(49,189), c(coef(dnac.0.2N.2.par)[2],coef(dnac.2.2N.2.par)[2])) nac.2.3 <- cbind(c(49,189), c(coef(dnac.0.2N.3.par)[2],coef(dnac.2.2N.3.par)[2])) nac.2.4 <- cbind(c(49,189), c(coef(dnac.0.2N.4.par)[2],coef(dnac.2.2N.4.par)[2])) nac.2.5 <- cbind(c(49,189), c(coef(dnac.0.2N.5.par)[2],coef(dnac.2.2N.5.par)[2])) lm.nac.1.1 <- lm(nac.1.1[,2]~nac.1.1[,1]) lm.nac.1.2 <- lm(nac.1.2[,2]~nac.1.2[,1]) lm.nac.1.3 <- lm(nac.1.3[,2]~nac.1.3[,1]) lm.nac.1.4 <- lm(nac.1.4[,2]~nac.1.4[,1]) lm.nac.1.5 <- lm(nac.1.5[,2]~nac.1.5[,1]) lm.nac.2.1 <- lm(nac.2.1[,2]~nac.2.1[,1]) lm.nac.2.2 <- lm(nac.2.2[,2]~nac.2.2[,1]) lm.nac.2.3 <- lm(nac.2.3[,2]~nac.2.3[,1]) lm.nac.2.4 <- lm(nac.2.4[,2]~nac.2.4[,1]) lm.nac.2.5 <- lm(nac.2.5[,2]~nac.2.5[,1]) lm.nac.1 <- c(lm.nac.1.1$coefficients[2] /6.7,lm.nac.1.2$coefficients[2] /6.7,lm.nac.1.3$coefficients[2] /6.7,lm.nac.1.4$coefficients[2] /6.7,lm.nac.1.5$coefficients[2] /6.7) lm.nac.2 <- c(lm.nac.2.1$coefficients[2] /6.7,lm.nac.2.2$coefficients[2] /6.7,lm.nac.2.3$coefficients[2] /6.7,lm.nac.2.4$coefficients[2] /6.7,lm.nac.2.5$coefficients[2] /6.7 ) lm.nac.1.ave <- mean(lm.nac.1) lm.nac.1.se <- se(lm.nac.1) lm.nac.2.ave <- mean(lm.nac.2) lm.nac.2.se <- se(lm.nac.2) nac.ttest <- t.test(lm.nac.1, lm.nac.2) nac.ttest #hcl dhcl<- subset(data, Enviro=="hcl") for (p in dhcl$Time){ nam <- paste("dhcl",p,sep=".") assign(nam, subset(dhcl, Time==p))} for (i in dhcl.0$Line){ name <- paste("dhcl.0",i,sep=".") dhcl.0.i <- assign(name, subset(dhcl.0, Line==i)) } dhcl.0.N <- subset(dhcl.0, Ploidy==1) dhcl.0.2N <- subset(dhcl.0, Ploidy==2) for (i in dhcl.0.N$Rep){ name <- paste("dhcl.0.N",i,sep=".") dhcl.0.N.i <- assign(name, subset(dhcl.0.N, Line==i)) } dhcl.0.N.5 <- subset(dhcl.0.N, Line==5) for (i in dhcl.0.2N$Rep){ name <- paste("dhcl.0.2N",i,sep=".") dhcl.0.2N.i <- assign(name, subset(dhcl.0.2N, Line==i)) } dhcl.0.2N.5 <- subset(dhcl.0.2N, Line==5) dhcl.2.N <- subset(dhcl.2, Ploidy==1) dhcl.2.2N <- subset(dhcl.2, Ploidy==2) for (i in dhcl.2.N$Line){ name <- paste("dhcl.2.N",i,sep=".") dhcl.2.N.i <- assign(name, subset(dhcl.2.N, Line==i)) } for (i in dhcl.2.2N$Line){ name <- paste("dhcl.2.2N",i,sep=".") dhcl.2.2N.i <- assign(name, subset(dhcl.2.2N, Line==i)) } eqn <- function(p0,sss,Day) ((p0*exp(sss*Day))/(1-p0+p0*exp(sss*Day))) p0s<-c() ssses<-c() namess<-c() dataset<-dhcl.0.N.1 funcnls<-function(dataset){ huh<-nls(DATA~eqn(p0,sss,Day), data=dataset, start=list(p0=0.4,sss=0.1))} dhcl.0.N.1.par <- funcnls(dhcl.0.N.1) dhcl.0.N.2.par <- funcnls(dhcl.0.N.2) dhcl.0.N.3.par <- funcnls(dhcl.0.N.3) dhcl.0.N.4.par <- funcnls(dhcl.0.N.4) dhcl.0.N.5.par <- funcnls(dhcl.0.N.5) dhcl.0.2N.1.par <- funcnls(dhcl.0.2N.1) dhcl.0.2N.2.par <- funcnls(dhcl.0.2N.2) dhcl.0.2N.3.par <- funcnls(dhcl.0.2N.3) dhcl.0.2N.4.par <- funcnls(dhcl.0.2N.4) dhcl.0.2N.5.par <- funcnls(dhcl.0.2N.5) dhcl.2.N.1.par <- funcnls(dhcl.2.N.1) dhcl.2.N.2.par <- funcnls(dhcl.2.N.2) dhcl.2.N.3.par <- funcnls(dhcl.2.N.3) dhcl.2.N.4.par <- funcnls(dhcl.2.N.4) dhcl.2.N.5.par <- funcnls(dhcl.2.N.5) dhcl.2.2N.1.par <- funcnls(dhcl.2.2N.1) dhcl.2.2N.2.par <- funcnls(dhcl.2.2N.2) dhcl.2.2N.3.par <- funcnls(dhcl.2.2N.3) dhcl.2.2N.4.par <- funcnls(dhcl.2.2N.4) dhcl.2.2N.5.par <- funcnls(dhcl.2.2N.5) hcl.1.1 <- cbind(c(49,189), c(coef(dhcl.0.N.1.par)[2],coef(dhcl.2.N.1.par)[2])) hcl.1.2 <- cbind(c(49,189), c(coef(dhcl.0.N.2.par)[2],coef(dhcl.2.N.2.par)[2])) hcl.1.3 <- cbind(c(49,189), c(coef(dhcl.0.N.3.par)[2],coef(dhcl.2.N.3.par)[2])) hcl.1.4 <- cbind(c(49,189), c(coef(dhcl.0.N.4.par)[2],coef(dhcl.2.N.4.par)[2])) hcl.1.5 <- cbind(c(49,189), c(coef(dhcl.0.N.5.par)[2],coef(dhcl.2.N.5.par)[2])) hcl.2.1 <- cbind(c(49,189), c(coef(dhcl.0.2N.1.par)[2],coef(dhcl.2.2N.1.par)[2])) hcl.2.2 <- cbind(c(49,189), c(coef(dhcl.0.2N.2.par)[2],coef(dhcl.2.2N.2.par)[2])) hcl.2.3 <- cbind(c(49,189), c(coef(dhcl.0.2N.3.par)[2],coef(dhcl.2.2N.3.par)[2])) hcl.2.4 <- cbind(c(49,189), c(coef(dhcl.0.2N.4.par)[2],coef(dhcl.2.2N.4.par)[2])) hcl.2.5 <- cbind(c(49,189), c(coef(dhcl.0.2N.5.par)[2],coef(dhcl.2.2N.5.par)[2])) lm.hcl.1.1 <- lm(hcl.1.1[,2]~hcl.1.1[,1]) lm.hcl.1.2 <- lm(hcl.1.2[,2]~hcl.1.2[,1]) lm.hcl.1.3 <- lm(hcl.1.3[,2]~hcl.1.3[,1]) lm.hcl.1.4 <- lm(hcl.1.4[,2]~hcl.1.4[,1]) lm.hcl.1.5 <- lm(hcl.1.5[,2]~hcl.1.5[,1]) lm.hcl.2.1 <- lm(hcl.2.1[,2]~hcl.2.1[,1]) lm.hcl.2.2 <- lm(hcl.2.2[,2]~hcl.2.2[,1]) lm.hcl.2.3 <- lm(hcl.2.3[,2]~hcl.2.3[,1]) lm.hcl.2.4 <- lm(hcl.2.4[,2]~hcl.2.4[,1]) lm.hcl.2.5 <- lm(hcl.2.5[,2]~hcl.2.5[,1]) lm.hcl.1 <- c(lm.hcl.1.1$coefficients[2] /6.7,lm.hcl.1.2$coefficients[2] /6.7,lm.hcl.1.3$coefficients[2] /6.7,lm.hcl.1.4$coefficients[2] /6.7,lm.hcl.1.5$coefficients[2] /6.7) lm.hcl.2 <- c(lm.hcl.2.1$coefficients[2] /6.7,lm.hcl.2.2$coefficients[2] /6.7,lm.hcl.2.3$coefficients[2] /6.7,lm.hcl.2.4$coefficients[2] /6.7,lm.hcl.2.5$coefficients[2] /6.7 ) lm.hcl.1.ave <- mean(lm.hcl.1) lm.hcl.1.se <- se(lm.hcl.1) lm.hcl.2.ave <- mean(lm.hcl.2) lm.hcl.2.se <- se(lm.hcl.2) hcl.ttest <- t.test(lm.hcl.1, lm.hcl.2) hcl.ttest #nystatin dnys<-subset(data,Enviro=="nys") for (p in dnys$Time){ nam <- paste("dnys",p,sep=".") assign(nam, subset(dnys, Time==p))} for (i in dnys.0$Line){ name <- paste("dnys.0",i,sep=".") dnys.0.i <- assign(name, subset(dnys.0, Line==i)) } dnys.0.N <- subset(dnys.0, Ploidy==1) dnys.0.2N <- subset(dnys.0, Ploidy==2) for (i in dnys.0.N$Rep){ name <- paste("dnys.0.N",i,sep=".") dnys.0.N.i <- assign(name, subset(dnys.0.N, Line==i)) } dnys.0.N.5 <- subset(dnys.0.N, Line==5) for (i in dnys.0.2N$Rep){ name <- paste("dnys.0.2N",i,sep=".") dnys.0.2N.i <- assign(name, subset(dnys.0.2N, Line==i)) } dnys.0.2N.5 <- subset(dnys.0.2N, Line==5) dnys.2.N <- subset(dnys.2, Ploidy==1) dnys.2.2N <- subset(dnys.2, Ploidy==2) for (i in dnys.2.N$Line){ name <- paste("dnys.2.N",i,sep=".") dnys.2.N.i <- assign(name, subset(dnys.2.N, Line==i)) } for (i in dnys.2.2N$Line){ name <- paste("dnys.2.2N",i,sep=".") dnys.2.2N.i <- assign(name, subset(dnys.2.2N, Line==i)) } eqn <- function(p0,sss,Day) ((p0*exp(sss*Day))/(1-p0+p0*exp(sss*Day))) p0s<-c() ssses<-c() namess<-c() dataset<-dnys.0.N.1 funcnls<-function(dataset){ huh<-nls(DATA~eqn(p0,sss,Day), data=dataset, start=list(p0=0.4,sss=0.1))} dnys.0.N.1.par <- funcnls(dnys.0.N.1) dnys.0.N.2.par <- funcnls(dnys.0.N.2) dnys.0.N.3.par <- funcnls(dnys.0.N.3) dnys.0.N.4.par <- funcnls(dnys.0.N.4) dnys.0.N.5.par <- funcnls(dnys.0.N.5) dnys.0.2N.1.par <- funcnls(dnys.0.2N.1) dnys.0.2N.2.par <- funcnls(dnys.0.2N.2) dnys.0.2N.3.par <- funcnls(dnys.0.2N.3) dnys.0.2N.4.par <- funcnls(dnys.0.2N.4) dnys.0.2N.5.par <- funcnls(dnys.0.2N.5) dnys.2.N.1.par <- funcnls(dnys.2.N.1) dnys.2.N.2.par <- funcnls(dnys.2.N.2) dnys.2.N.3.par <- funcnls(dnys.2.N.3) dnys.2.N.4.par <- funcnls(dnys.2.N.4) dnys.2.N.5.par <- funcnls(dnys.2.N.5) dnys.2.2N.1.par <- funcnls(dnys.2.2N.1) dnys.2.2N.2.par <- funcnls(dnys.2.2N.2) dnys.2.2N.3.par <- funcnls(dnys.2.2N.3) dnys.2.2N.4.par <- funcnls(dnys.2.2N.4) dnys.2.2N.5.par <- funcnls(dnys.2.2N.5) nys.1.1 <- cbind(c(49,189), c(coef(dnys.0.N.1.par)[2],coef(dnys.2.N.1.par)[2])) nys.1.2 <- cbind(c(49,189), c(coef(dnys.0.N.2.par)[2],coef(dnys.2.N.2.par)[2])) nys.1.3 <- cbind(c(49,189), c(coef(dnys.0.N.3.par)[2],coef(dnys.2.N.3.par)[2])) nys.1.4 <- cbind(c(49,189), c(coef(dnys.0.N.4.par)[2],coef(dnys.2.N.4.par)[2])) nys.1.5 <- cbind(c(49,189), c(coef(dnys.0.N.5.par)[2],coef(dnys.2.N.5.par)[2])) nys.2.1 <- cbind(c(49,189), c(coef(dnys.0.2N.1.par)[2],coef(dnys.2.2N.1.par)[2])) nys.2.2 <- cbind(c(49,189), c(coef(dnys.0.2N.2.par)[2],coef(dnys.2.2N.2.par)[2])) nys.2.3 <- cbind(c(49,189), c(coef(dnys.0.2N.3.par)[2],coef(dnys.2.2N.3.par)[2])) nys.2.4 <- cbind(c(49,189), c(coef(dnys.0.2N.4.par)[2],coef(dnys.2.2N.4.par)[2])) nys.2.5 <- cbind(c(49,189), c(coef(dnys.0.2N.5.par)[2],coef(dnys.2.2N.5.par)[2])) lm.nys.1.1 <- lm(nys.1.1[,2]~nys.1.1[,1]) lm.nys.1.2 <- lm(nys.1.2[,2]~nys.1.2[,1]) lm.nys.1.3 <- lm(nys.1.3[,2]~nys.1.3[,1]) lm.nys.1.4 <- lm(nys.1.4[,2]~nys.1.4[,1]) lm.nys.1.5 <- lm(nys.1.5[,2]~nys.1.5[,1]) lm.nys.2.1 <- lm(nys.2.1[,2]~nys.2.1[,1]) lm.nys.2.2 <- lm(nys.2.2[,2]~nys.2.2[,1]) lm.nys.2.3 <- lm(nys.2.3[,2]~nys.2.3[,1]) lm.nys.2.4 <- lm(nys.2.4[,2]~nys.2.4[,1]) lm.nys.2.5 <- lm(nys.2.5[,2]~nys.2.5[,1]) lm.nys.1 <- c(lm.nys.1.1$coefficients[2] /6.7,lm.nys.1.2$coefficients[2] /6.7,lm.nys.1.3$coefficients[2] /6.7,lm.nys.1.4$coefficients[2] /6.7,lm.nys.1.5$coefficients[2] /6.7) lm.nys.2 <- c(lm.nys.2.1$coefficients[2]/6.7,lm.nys.2.2$coefficients[2]/6.7,lm.nys.2.3$coefficients[2]/6.7,lm.nys.2.4$coefficients[2]/6.7,lm.nys.2.5$coefficients[2]/6.7) lm.nys.1.ave <- mean(lm.nys.1) lm.nys.1.se <- se(lm.nys.1) lm.nys.2.ave <- mean(lm.nys.2) lm.nys.2.se <- se(lm.nys.2) nys.ttest <- t.test(lm.nys.1, lm.nys.2, var.equal=T) nys.ttest #ethanol deth<-subset(data, Enviro=="eth") for (p in deth$Time){ nam <- paste("deth",p,sep=".") assign(nam, subset(deth, Time==p))} for (i in deth.0$Line){ name <- paste("deth.0",i,sep=".") deth.0.i <- assign(name, subset(deth.0, Line==i)) } deth.0.N <- subset(deth.0, Ploidy==1) deth.0.2N <- subset(deth.0, Ploidy==2) for (i in deth.0.N$Rep){ name <- paste("deth.0.N",i,sep=".") deth.0.N.i <- assign(name, subset(deth.0.N, Line==i)) } deth.0.N.5 <- subset(deth.0.N, Line==5) for (i in deth.0.2N$Rep){ name <- paste("deth.0.2N",i,sep=".") deth.0.2N.i <- assign(name, subset(deth.0.2N, Line==i)) } deth.0.2N.5 <- subset(deth.0.2N, Line==5) deth.2.N <- subset(deth.2, Ploidy==1) deth.2.2N <- subset(deth.2, Ploidy==2) for (i in deth.2.N$Line){ name <- paste("deth.2.N",i,sep=".") deth.2.N.i <- assign(name, subset(deth.2.N, Line==i)) } for (i in deth.2.2N$Line){ name <- paste("deth.2.2N",i,sep=".") deth.2.2N.i <- assign(name, subset(deth.2.2N, Line==i)) } eqn <- function(p0,sss,Day) ((p0*exp(sss*Day))/(1-p0+p0*exp(sss*Day))) p0s<-c() ssses<-c() namess<-c() dataset<-deth.0.N.1 funcnls<-function(dataset){ huh<-nls(DATA~eqn(p0,sss,Day), data=dataset, start=list(p0=0.4,sss=0.1))} deth.0.N.1.par <- funcnls(deth.0.N.1) deth.0.N.2.par <- funcnls(deth.0.N.2) deth.0.N.3.par <- funcnls(deth.0.N.3) deth.0.N.4.par <- funcnls(deth.0.N.4) deth.0.N.5.par <- funcnls(deth.0.N.5) deth.0.2N.1.par <- funcnls(deth.0.2N.1) deth.0.2N.2.par <- funcnls(deth.0.2N.2) deth.0.2N.3.par <- funcnls(deth.0.2N.3) deth.0.2N.4.par <- funcnls(deth.0.2N.4) deth.0.2N.5.par <- funcnls(deth.0.2N.5) deth.2.N.1.par <- funcnls(deth.2.N.1) deth.2.N.2.par <- funcnls(deth.2.N.2) deth.2.N.3.par <- funcnls(deth.2.N.3) deth.2.N.4.par <- funcnls(deth.2.N.4) deth.2.N.5.par <- funcnls(deth.2.N.5) deth.2.2N.1.par <- funcnls(deth.2.2N.1) deth.2.2N.2.par <- funcnls(deth.2.2N.2) deth.2.2N.3.par <- funcnls(deth.2.2N.3) deth.2.2N.4.par <- funcnls(deth.2.2N.4) deth.2.2N.5.par <- funcnls(deth.2.2N.5) eth.1.1 <- cbind(c(49,189), c(coef(deth.0.N.1.par)[2],coef(deth.2.N.1.par)[2])) eth.1.2 <- cbind(c(49,189), c(coef(deth.0.N.2.par)[2],coef(deth.2.N.2.par)[2])) eth.1.3 <- cbind(c(49,189), c(coef(deth.0.N.3.par)[2],coef(deth.2.N.3.par)[2])) eth.1.4 <- cbind(c(49,189), c(coef(deth.0.N.4.par)[2],coef(deth.2.N.4.par)[2])) eth.1.5 <- cbind(c(49,189), c(coef(deth.0.N.5.par)[2],coef(deth.2.N.5.par)[2])) eth.2.1 <- cbind(c(49,189), c(coef(deth.0.2N.1.par)[2],coef(deth.2.2N.1.par)[2])) eth.2.2 <- cbind(c(49,189), c(coef(deth.0.2N.2.par)[2],coef(deth.2.2N.2.par)[2])) eth.2.3 <- cbind(c(49,189), c(coef(deth.0.2N.3.par)[2],coef(deth.2.2N.3.par)[2])) eth.2.4 <- cbind(c(49,189), c(coef(deth.0.2N.4.par)[2],coef(deth.2.2N.4.par)[2])) eth.2.5 <- cbind(c(49,189), c(coef(deth.0.2N.5.par)[2],coef(deth.2.2N.5.par)[2])) lm.eth.1.1 <- lm(eth.1.1[,2]~eth.1.1[,1]) lm.eth.1.2 <- lm(eth.1.2[,2]~eth.1.2[,1]) lm.eth.1.3 <- lm(eth.1.3[,2]~eth.1.3[,1]) lm.eth.1.4 <- lm(eth.1.4[,2]~eth.1.4[,1]) lm.eth.1.5 <- lm(eth.1.5[,2]~eth.1.5[,1]) lm.eth.2.1 <- lm(eth.2.1[,2]~eth.2.1[,1]) lm.eth.2.2 <- lm(eth.2.2[,2]~eth.2.2[,1]) lm.eth.2.3 <- lm(eth.2.3[,2]~eth.2.3[,1]) lm.eth.2.4 <- lm(eth.2.4[,2]~eth.2.4[,1]) lm.eth.2.5 <- lm(eth.2.5[,2]~eth.2.5[,1]) lm.eth.1 <- c(lm.eth.1.1$coefficients[2]/6.7,lm.eth.1.2$coefficients[2] /6.7,lm.eth.1.3$coefficients[2]/6.7,lm.eth.1.4$coefficients[2] /6.7,lm.eth.1.5$coefficients[2]/6.7) lm.eth.2 <- c(lm.eth.2.1$coefficients[2] /6.7,lm.eth.2.2$coefficients[2] /6.7,lm.eth.2.3$coefficients[2] /6.7,lm.eth.2.4$coefficients[2] /6.7,lm.eth.2.5$coefficients[2] /6.7 ) lm.eth.1.ave <- mean(lm.eth.1) lm.eth.1.se <- se(lm.eth.1) lm.eth.2.ave <- mean(lm.eth.2) lm.eth.2.se <- se(lm.eth.2) eth.ttest <- t.test(lm.eth.1, lm.eth.2) eth.ttest #koh dkoh<-subset(data, Enviro=="koh") for (p in dkoh$Time){ nam <- paste("dkoh",p,sep=".") assign(nam, subset(dkoh, Time==p))} for (i in dkoh.0$Line){ name <- paste("dkoh.0",i,sep=".") dkoh.0.i <- assign(name, subset(dkoh.0, Line==i)) } dkoh.0.N <- subset(dkoh.0, Ploidy==1) dkoh.0.2N <- subset(dkoh.0, Ploidy==2) for (i in dkoh.0.N$Rep){ name <- paste("dkoh.0.N",i,sep=".") dkoh.0.N.i <- assign(name, subset(dkoh.0.N, Line==i)) } dkoh.0.N.5 <- subset(dkoh.0.N, Line==5) for (i in dkoh.0.2N$Rep){ name <- paste("dkoh.0.2N",i,sep=".") dkoh.0.2N.i <- assign(name, subset(dkoh.0.2N, Line==i)) } dkoh.0.2N.5 <- subset(dkoh.0.2N, Line==5) dkoh.2.N <- subset(dkoh.2, Ploidy==1) dkoh.2.2N <- subset(dkoh.2, Ploidy==2) for (i in dkoh.2.N$Line){ name <- paste("dkoh.2.N",i,sep=".") dkoh.2.N.i <- assign(name, subset(dkoh.2.N, Line==i)) } for (i in dkoh.2.2N$Line){ name <- paste("dkoh.2.2N",i,sep=".") dkoh.2.2N.i <- assign(name, subset(dkoh.2.2N, Line==i)) } eqn <- function(p0,sss,Day) ((p0*exp(sss*Day))/(1-p0+p0*exp(sss*Day))) p0s<-c() ssses<-c() namess<-c() dataset<-dkoh.0.N.1 funcnls<-function(dataset){ huh<-nls(DATA~eqn(p0,sss,Day), data=dataset, start=list(p0=0.4,sss=0.1))} dkoh.0.N.1.par <- funcnls(dkoh.0.N.1) dkoh.0.N.2.par <- funcnls(dkoh.0.N.2) dkoh.0.N.3.par <- funcnls(dkoh.0.N.3) dkoh.0.N.4.par <- funcnls(dkoh.0.N.4) dkoh.0.N.5.par <- funcnls(dkoh.0.N.5) dkoh.0.2N.1.par <- funcnls(dkoh.0.2N.1) dkoh.0.2N.2.par <- funcnls(dkoh.0.2N.2) dkoh.0.2N.3.par <- funcnls(dkoh.0.2N.3) dkoh.0.2N.4.par <- funcnls(dkoh.0.2N.4) dkoh.0.2N.5.par <- funcnls(dkoh.0.2N.5) dkoh.2.N.1.par <- funcnls(dkoh.2.N.1) dkoh.2.N.2.par <- funcnls(dkoh.2.N.2) dkoh.2.N.3.par <- funcnls(dkoh.2.N.3) dkoh.2.N.4.par <- funcnls(dkoh.2.N.4) dkoh.2.N.5.par <- funcnls(dkoh.2.N.5) dkoh.2.2N.1.par <- funcnls(dkoh.2.2N.1) dkoh.2.2N.2.par <- funcnls(dkoh.2.2N.2) dkoh.2.2N.3.par <- funcnls(dkoh.2.2N.3) dkoh.2.2N.4.par <- funcnls(dkoh.2.2N.4) dkoh.2.2N.5.par <- funcnls(dkoh.2.2N.5) koh.1.1 <- cbind(c(49,189), c(coef(dkoh.0.N.1.par)[2],coef(dkoh.2.N.1.par)[2])) koh.1.2 <- cbind(c(49,189), c(coef(dkoh.0.N.2.par)[2],coef(dkoh.2.N.2.par)[2])) koh.1.3 <- cbind(c(49,189), c(coef(dkoh.0.N.3.par)[2],coef(dkoh.2.N.3.par)[2])) koh.1.4 <- cbind(c(49,189), c(coef(dkoh.0.N.4.par)[2],coef(dkoh.2.N.4.par)[2])) koh.1.5 <- cbind(c(49,189), c(coef(dkoh.0.N.5.par)[2],coef(dkoh.2.N.5.par)[2])) koh.2.1 <- cbind(c(49,189), c(coef(dkoh.0.2N.1.par)[2],coef(dkoh.2.2N.1.par)[2])) koh.2.2 <- cbind(c(49,189), c(coef(dkoh.0.2N.2.par)[2],coef(dkoh.2.2N.2.par)[2])) koh.2.3 <- cbind(c(49,189), c(coef(dkoh.0.2N.3.par)[2],coef(dkoh.2.2N.3.par)[2])) koh.2.4 <- cbind(c(49,189), c(coef(dkoh.0.2N.4.par)[2],coef(dkoh.2.2N.4.par)[2])) koh.2.5 <- cbind(c(49,189), c(coef(dkoh.0.2N.5.par)[2],coef(dkoh.2.2N.5.par)[2])) lm.koh.1.1 <- lm(koh.1.1[,2]~koh.1.1[,1]) lm.koh.1.2 <- lm(koh.1.2[,2]~koh.1.2[,1]) lm.koh.1.3 <- lm(koh.1.3[,2]~koh.1.3[,1]) lm.koh.1.4 <- lm(koh.1.1[,2]~koh.1.4[,1]) lm.koh.1.5 <- lm(koh.1.5[,2]~koh.1.5[,1]) lm.koh.2.1 <- lm(koh.2.1[,2]~koh.2.1[,1]) lm.koh.2.2 <- lm(koh.2.1[,2]~koh.2.2[,1]) lm.koh.2.3 <- lm(koh.2.3[,2]~koh.2.3[,1]) lm.koh.2.4 <- lm(koh.2.4[,2]~koh.2.4[,1]) lm.koh.2.5 <- lm(koh.2.5[,2]~koh.2.5[,1]) lm.koh.1 <- c(lm.koh.1.1$coefficients[2] /6.7,lm.koh.1.2$coefficients[2] /6.7,lm.koh.1.3$coefficients[2] /6.7,lm.koh.1.4$coefficients[2] /6.7,lm.koh.1.5$coefficients[2] /6.7 ) lm.koh.2 <- c(lm.koh.2.1$coefficients[2] /6.7,lm.koh.2.2$coefficients[2] /6.7,lm.koh.2.3$coefficients[2] /6.7,lm.koh.2.4$coefficients[2] /6.7,lm.koh.2.5$coefficients[2] /6.7) lm.koh.1.ave <- mean(lm.koh.1) lm.koh.1.se <- se(lm.koh.1) lm.koh.2.ave <- mean(lm.koh.2) lm.koh.2.se <- se(lm.koh.2) koh.ttest <- t.test(lm.koh.1, lm.koh.2) koh.ttest #caffeine dcaf<-subset(data, Enviro=="caf") for (p in dcaf$Time){ nam <- paste("dcaf",p,sep=".") assign(nam, subset(dcaf, Time==p))} for (i in dcaf.0$Line){ name <- paste("dcaf.0",i,sep=".") dcaf.0.i <- assign(name, subset(dcaf.0, Line==i)) } dcaf.0.N <- subset(dcaf.0, Ploidy==1) dcaf.0.2N <- subset(dcaf.0, Ploidy==2) for (i in dcaf.0.N$Rep){ name <- paste("dcaf.0.N",i,sep=".") dcaf.0.N.i <- assign(name, subset(dcaf.0.N, Line==i)) } dcaf.0.N.5 <- subset(dcaf.0.N, Line==5) for (i in dcaf.0.2N$Rep){ name <- paste("dcaf.0.2N",i,sep=".") dcaf.0.2N.i <- assign(name, subset(dcaf.0.2N, Line==i)) } dcaf.0.2N.5 <- subset(dcaf.0.2N, Line==5) dcaf.2.N <- subset(dcaf.2, Ploidy==1) dcaf.2.2N <- subset(dcaf.2, Ploidy==2) for (i in dcaf.2.N$Line){ name <- paste("dcaf.2.N",i,sep=".") dcaf.2.N.i <- assign(name, subset(dcaf.2.N, Line==i)) } for (i in dcaf.2.2N$Line){ name <- paste("dcaf.2.2N",i,sep=".") dcaf.2.2N.i <- assign(name, subset(dcaf.2.2N, Line==i)) } eqn <- function(p0,sss,Day) ((p0*exp(sss*Day))/(1-p0+p0*exp(sss*Day))) p0s<-c() ssses<-c() namess<-c() dataset<-dcaf.0.N.1 funcnls<-function(dataset){ huh<-nls(DATA~eqn(p0,sss,Day), data=dataset, start=list(p0=0.4,sss=0.1))} dcaf.0.N.1.par <- funcnls(dcaf.0.N.1) dcaf.0.N.2.par <- funcnls(dcaf.0.N.2) dcaf.0.N.3.par <- funcnls(dcaf.0.N.3) dcaf.0.N.4.par <- funcnls(dcaf.0.N.4) dcaf.0.N.5.par <- funcnls(dcaf.0.N.5) dcaf.0.2N.1.par <- funcnls(dcaf.0.2N.1) dcaf.0.2N.2.par <- funcnls(dcaf.0.2N.2) dcaf.0.2N.3.par <- funcnls(dcaf.0.2N.3) dcaf.0.2N.4.par <- funcnls(dcaf.0.2N.4) dcaf.0.2N.5.par <- funcnls(dcaf.0.2N.5) dcaf.2.N.1.par <- funcnls(dcaf.2.N.1) dcaf.2.N.2.par <- funcnls(dcaf.2.N.2) dcaf.2.N.3.par <- funcnls(dcaf.2.N.3) dcaf.2.N.4.par <- funcnls(dcaf.2.N.4) dcaf.2.N.5.par <- funcnls(dcaf.2.N.5) dcaf.2.2N.1.par <- funcnls(dcaf.2.2N.1) dcaf.2.2N.2.par <- funcnls(dcaf.2.2N.2) dcaf.2.2N.3.par <- funcnls(dcaf.2.2N.3) dcaf.2.2N.4.par <- funcnls(dcaf.2.2N.4) dcaf.2.2N.5.par <- funcnls(dcaf.2.2N.5) caf.1.1 <- cbind(c(49,189), c(coef(dcaf.0.N.1.par)[2],coef(dcaf.2.N.1.par)[2])) caf.1.2 <- cbind(c(49,189), c(coef(dcaf.0.N.2.par)[2],coef(dcaf.2.N.2.par)[2])) caf.1.3 <- cbind(c(49,189), c(coef(dcaf.0.N.3.par)[2],coef(dcaf.2.N.3.par)[2])) caf.1.4 <- cbind(c(49,189), c(coef(dcaf.0.N.4.par)[2],coef(dcaf.2.N.4.par)[2])) caf.1.5 <- cbind(c(49,189), c(coef(dcaf.0.N.5.par)[2],coef(dcaf.2.N.5.par)[2])) caf.2.1 <- cbind(c(49,189), c(coef(dcaf.0.2N.1.par)[2],coef(dcaf.2.2N.1.par)[2])) caf.2.2 <- cbind(c(49,189), c(coef(dcaf.0.2N.2.par)[2],coef(dcaf.2.2N.2.par)[2])) caf.2.3 <- cbind(c(49,189), c(coef(dcaf.0.2N.3.par)[2],coef(dcaf.2.2N.3.par)[2])) caf.2.4 <- cbind(c(49,189), c(coef(dcaf.0.2N.4.par)[2],coef(dcaf.2.2N.4.par)[2])) caf.2.5 <- cbind(c(49,189), c(coef(dcaf.0.2N.5.par)[2],coef(dcaf.2.2N.5.par)[2])) lm.caf.1.1 <- lm(caf.1.1[,2]~caf.1.1[,1]) lm.caf.1.2 <- lm(caf.1.2[,2]~caf.1.2[,1]) lm.caf.1.3 <- lm(caf.1.3[,2]~caf.1.3[,1]) lm.caf.1.4 <- lm(caf.1.4[,2]~caf.1.4[,1]) lm.caf.1.5 <- lm(caf.1.5[,2]~caf.1.5[,1]) lm.caf.2.1 <- lm(caf.2.1[,2]~caf.2.1[,1]) lm.caf.2.2 <- lm(caf.2.2[,2]~caf.2.2[,1]) lm.caf.2.3 <- lm(caf.2.3[,2]~caf.2.3[,1]) lm.caf.2.4 <- lm(caf.2.4[,2]~caf.2.4[,1]) lm.caf.2.5 <- lm(caf.2.5[,2]~caf.2.5[,1]) lm.caf.1 <- c(lm.caf.1.1$coefficients[2] /6.7,lm.caf.1.2$coefficients[2] /6.7,lm.caf.1.3$coefficients[2] /6.7,lm.caf.1.4$coefficients[2] /6.7,lm.caf.1.5$coefficients[2] /6.7) lm.caf.2 <- c(lm.caf.2.1$coefficients[2] /6.7,lm.caf.2.2$coefficients[2] /6.7,lm.caf.2.3$coefficients[2] /6.7,lm.caf.2.4$coefficients[2] /6.7,lm.caf.2.5$coefficients[2] /6.7) lm.caf.1.ave <- mean(lm.caf.1) lm.caf.1.se <- se(lm.caf.1) lm.caf.2.ave <- mean(lm.caf.2) lm.caf.2.se <- se(lm.caf.2) caf.ttest <- t.test(lm.caf.1, lm.caf.2, var.equal=T) caf.ttest #stats #lm parameters lmypd <- data.frame(c("N","N","N","N","2N","2N","2N","2N","2N"),c(1,2,3,5,1,2,3,4,5),c(lm.ypd.1, lm.ypd.2),c("YPD")) names(lmypd)<-c("Ploidy","Line","lm","Enviro") fligner.test(lmypd[,3],lmypd[,1]) #not sig diff ypd.ttest<- t.test(lm.ypd.1, lm.ypd.2, var.equal=T) ypd.ttest ypd.2N <- subset(lmypd, Ploidy=="2N") ypd.t.2N <- t.test(ypd.2N$lm, mu=0) lmkoh <- data.frame(c("N","N","N","N","N","2N","2N","2N","2N","2N"),c(1,2,3,4,5,1,2,3,4,5),c(lm.koh.1, lm.koh.2),c("koh")) names(lmkoh)<-c("Ploidy","Line","lm","Enviro") fligner.test(lmkoh[,3],lmkoh[,1]) #not sig diff koh.ttest<- t.test(lm.koh.1, lm.koh.2, var.equal=T) koh.ttest koh.2N <- subset(lmkoh, Ploidy=="2N") koh.t.2N <- t.test(koh.2N$lm, mu=0) lmeth <- data.frame(c("N","N","N","N","N","2N","2N","2N","2N","2N"),c(1,2,3,4,5,1,2,3,4,5),c(lm.eth.1, lm.eth.2),c("eth")) names(lmeth)<-c("Ploidy","Line","lm","Enviro") fligner.test(lmeth[,3],lmeth[,1]) #not sig diff eth.ttest<- t.test(lm.eth.1, lm.eth.2, var.equal=T) eth.ttest eth.2N <- subset(lmeth, Ploidy=="2N") eth.t.2N <- t.test(eth.2N$lm, mu=0) lmnac <- data.frame(c("N","N","N","N","N","2N","2N","2N","2N","2N"),c(1,2,3,4,5,1,2,3,4,5),c(lm.nac.1, lm.nac.2),c("nac")) names(lmnac)<-c("Ploidy","Line","lm","Enviro") fligner.test(lmnac[,3],lmnac[,1]) #not sig diff nac.ttest<- t.test(lm.nac.1, lm.nac.2, var.equal=T) nac.ttest nac.2N <- subset(lmnac, Ploidy=="2N") nac.t.2N <- t.test(nac.2N$lm, mu=0) lmhcl <- data.frame(c("N","N","N","N","N","2N","2N","2N","2N","2N"),c(1,2,3,4,5,1,2,3,4,5),c(lm.hcl.1, lm.hcl.2),c("hcl")) names(lmhcl)<-c("Ploidy","Line","lm","Enviro") fligner.test(lmhcl[,3],lmhcl[,1]) #not sig diff hcl.ttest<- t.test(lm.hcl.1, lm.hcl.2, var.equal=T) hcl.ttest hcl.2N <- subset(lmhcl, Ploidy=="2N") hcl.t.2N <- t.test(hcl.2N$lm, mu=0) lmnys <- data.frame(c("N","N","N","N","N","2N","2N","2N","2N","2N"),c(1,2,3,4,5,1,2,3,4,5),c(lm.nys.1, lm.nys.2),c("nys")) names(lmnys)<-c("Ploidy","Line","lm","Enviro") fligner.test(lmnys[,3],lmnys[,1]) #not sig diff nys.ttest<- t.test(lm.nys.1, lm.nys.2, var.equal=T) nys.ttest nys.2N <- subset(lmnys, Ploidy=="2N") nys.t.2N <- t.test(nys.2N$lm, mu=0) lmcaf <- data.frame(c("N","N","N","N","N","2N","2N","2N","2N","2N"),c(1,2,3,4,5,1,2,3,4,5),c(lm.caf.1, lm.caf.2),c("caf")) names(lmcaf)<-c("Ploidy","Line","lm","Enviro") fligner.test(lmcaf[,3],lmcaf[,1])#not sig diff caf.ttest<- t.test(lm.caf.1, lm.caf.2, var.equal=T) caf.ttest caf.2N <- subset(lmcaf, Ploidy=="2N") caf.t.2N <- t.test(caf.2N$lm, mu=0) #Paper graphs (black and white) #slopes #Graph Slopes mean lm.hap <- c(lm.ypd.1.ave, lm.hcl.1.ave,lm.eth.1.ave,lm.koh.1.ave,lm.nys.1.ave,lm.nac.1.ave,lm.caf.1.ave) lm.dip <- c(lm.ypd.2.ave, lm.hcl.2.ave,lm.eth.2.ave,lm.koh.2.ave,lm.nys.2.ave,lm.nac.2.ave,lm.caf.2.ave) lm.hap.se <- c(lm.ypd.1.se, lm.hcl.1.se,lm.eth.1.se,lm.koh.1.se,lm.nys.1.se,lm.nac.1.se,lm.caf.1.se) lm.dip.se <- c(lm.ypd.2.se, lm.hcl.2.se,lm.eth.2.se,lm.koh.2.se,lm.nys.2.se,lm.nac.2.se,lm.caf.2.se) enviro <- c("YPD","HCl","Ethanol","KOH","Nystatin","NaCl","Caffeine") lm.data <- data.frame(enviro,lm.hap,lm.dip,lm.hap.se,lm.dip.se) lm.data$enviro <- factor(lm.data$enviro, levels=unique(as.character(lm.data$enviro))) # Black and White pdf("figure1", width=6.5, height=4, family="Times", pointsize=9) par(mar=c(5,7,1,1)) plot(1:7,lm.hap, xaxt="n",,pch=21, ylab="", xlab="Environment (stressor + YPD)", cex=2, cex.axis=1.2, cex.lab=1.3, xlim=c(0.85,7.15), ylim=c(-0.0001,0.0015), type="n", yaxt="n") axis(1,at=c(1.05,2.05,3.05,4.05,5.05,6.05, 7.05),labels=c("YPD","HCl","Ethanol","KOH","Nystatin","NaCl","Caffeine"), cex.axis=1.2, cex.lab=1.2) title(ylab="Rate of adaptation (/generation)", line=5, cex.lab=1.3) axis(2, las=2, cex.axis=1.2) segments(c(1:7),lm.hap-lm.hap.se,c(1:7),lm.hap+lm.hap.se) points(c(1:7)+0.1,lm.dip, pch=19, col="black",cex=2.8) points(c(1:7),lm.hap, pch=21, cex=2.8) segments(c(1:7)+0.1,lm.dip-lm.dip.se,c(1:7)+0.1,lm.dip+lm.dip.se, col="black") text(0.8,lm.hap[1],labels="*",cex=2) #YPd text(5.8,lm.hap[6],labels="*",cex=2) #NaCl text(2.8,lm.hap[3],labels="*",cex=2) #Ethanol legend(0.8, 0.0015 ,legend=c("haploid", "diploid"),col=c("black","black"),pch=c(21,19),xjust=0,cex=1.4) abline(h=0, lty=2) dev.off() system("open figure1")