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R/plot_EIC.R
In MetaboList: Annotation of Metabolites from Liquid Chromatography-Mass Spectrometry Data
Defines functions
plot_EIC
Documented in
plot_EIC
plot_EIC<-function(fullms,peakID=333,ms=1,CE=0){
if(ms==1){
if (is.numeric(peakID) == FALSE) {
for (i in fullms$ms$peakID){
peak <- fullms$RawData1[which(fullms$RawData1[,7] == i), ]
peak<-as.data.frame(peak)
npeak<-peak[order(peak$RT),]
p3 <- ggplot(data =npeak,aes(npeak$RT/60 ,y=npeak$intensity))+
geom_area(data=npeak,aes(x=npeak$RT/60,y=npeak$intensity),fill="#00BFC4",alpha = 0.5,color="darkcyan")
p3b<-p3+theme_light()+theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3b+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Raw:",fullms$ms$name[fullms$ms$peakID==i]))
ggsave(plot,filename=paste(i,"Raw.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
npeak<-as.data.frame(npeak)
# predict<-cbind(npeak,predict(fit))
#fit.bs<-lm(npeak$intensity~ bs(npeak$RT/60))
#lines(npeak$RT/60,predict(fit.bs,data.frame(x=npeak$RT/60)),col=2,lwd=2)
npeakRT<-npeak$RT/60
p3 <- ggplot(data =npeak,aes(x=npeakRT,y=npeak$intensity))+ geom_point()+
geom_smooth(method = "loess",se=F)+theme_light()+
geom_ribbon(aes(ymin=0,ymax=predict(loess(npeak$intensity~npeakRT))),fill="#00BFC4",alpha = 0.5)+
theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Smooth:",fullms$ms$name[fullms$ms$peakID==i]))
ggsave(plot,filename=paste(i,"Smooth.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
diff<-diff(npeak$`m/z`)*100
tiff(filename=paste(i,"Scan.pdf",sep=""), res = 800, width = 6, height = 4, units = 'in')
plot(diff,type="h",xlab="Scan",ylab="m/z difference",cex.lab=1.5,lwd=5,col="cyan3",panel.first=grid(lty=1))
abline(h=mean(diff),col="#3366FF",lwd=3, lty=2)
abline(h=0,col="black")
title(main=paste("QC m/z scan:",fullms$ms$name[fullms$ms$peakID==i]))
dev.off()
}}else {
i=peakID
peak <- fullms$RawData[which(fullms$RawData[,7] == i), ]
peak<-as.data.frame(peak)
npeak<-peak[order(peak$RT),]
npeakRT<-npeak$RT/60
p3 <- ggplot(data =npeak,aes(npeak$RT/60 ,y=npeak$intensity))+
geom_area(data=npeak,aes(x=npeak$RT/60,y=npeak$intensity),fill="#00BFC4",alpha = 0.5,color="darkcyan")
p3b<-p3+theme_light()+theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3b+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Raw:",fullms$ms$name[fullms$ms$peakID==i]))
ggsave(plot,filename=paste(i,"Raw.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
p3 <- ggplot(data =npeak,aes(x=npeakRT,y=npeak$intensity))+ geom_point()+
geom_smooth(method = "loess",se=F)+theme_light()+
geom_ribbon(aes(ymin=0,ymax=predict(loess(npeak$intensity~npeakRT))),fill="#00BFC4",alpha = 0.5)+
theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Smooth:",fullms$ms$name[fullms$ms$peakID==i]))
ggsave(plot,filename=paste(i,"Smooth.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
diff<-diff(npeak$`m/z`)*100
tiff(filename=paste(i,"Scan.tiff",sep=""), res = 800, width = 6, height = 4, units = 'in')
plot(diff,type="h",xlab="Scan",ylab="m/z difference",cex.lab=1.5,lwd=5,col="cyan3",panel.first=grid(lty=1))
abline(h=mean(diff),col="#3366FF",lwd=3, lty=2)
abline(h=0,col="black")
title(main=paste("QC m/z scan:",fullms$ms$name[fullms$ms$peakID==i]))
dev.off()
}}else{
if(CE==0){
## here is for ms1 from DIA experiment
if (is.numeric(peakID) == FALSE) {
for (i in fullms$annotation$PeakID){
peak <- fullms$RawData1[which(fullms$RawData1[,7] == i), ]
peak<-as.data.frame(peak)
npeak<-peak[order(peak$RT),]
p3 <- ggplot(data =npeak,aes(npeak$RT/60 ,y=npeak$intensity))+
geom_area(data=npeak,aes(x=npeak$RT/60,y=npeak$intensity),fill="#00BFC4",alpha = 0.5,color="darkcyan")
p3b<-p3+theme_light()+theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3b+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Raw:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
ggsave(plot,filename=paste(i,"Raw.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
npeak<-as.data.frame(npeak)
# predict<-cbind(npeak,predict(fit))
#fit.bs<-lm(npeak$intensity~ bs(npeak$RT/60))
#lines(npeak$RT/60,predict(fit.bs,data.frame(x=npeak$RT/60)),col=2,lwd=2)
npeakRT<-npeak$RT/60
p3 <- ggplot(data =npeak,aes(x=npeakRT,y=npeak$intensity))+ geom_point()+
geom_smooth(method = "loess",se=F)+theme_light()+
geom_ribbon(aes(ymin=0,ymax=predict(loess(npeak$intensity~npeakRT))),fill="#00BFC4",alpha = 0.5)+
theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Smooth:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
ggsave(plot,filename=paste(i,"Smooth.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
#
diff<-diff(npeak$`m/z`)*100
pdf(file=paste(i,"Scan.pdf",sep=""))
plot(diff,type="h",xlab="Scan",ylab="m/z difference",cex.lab=1.5,lwd=5,col="cyan3",panel.first=grid(lty=1))
abline(h=mean(diff),col="#3366FF",lwd=3, lty=2)
abline(h=0,col="black")
title(main=paste("QC m/z scan:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
dev.off()
}}
else {
i=peakID
peak <- fullms$RawData1[which(fullms$RawData1[,7] == i), ]
peak<-as.data.frame(peak)
npeak<-peak[order(peak$RT),]
npeakRT<-npeak$RT/60
p3 <- ggplot(data =npeak,aes(npeak$RT/60 ,y=npeak$intensity))+
geom_area(data=npeak,aes(x=npeak$RT/60,y=npeak$intensity),fill="#00BFC4",alpha = 0.5,color="darkcyan")
p3b<-p3+theme_light()+theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3b+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Raw:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
ggsave(plot,filename=paste(i,"Raw.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
npeak<-as.data.frame(npeak)
#predict<-cbind(npeak,predict(fit))
#fit.bs<-lm(npeak$intensity~ bs(npeak$RT/60))
#lines(npeak$RT/60,predict(fit.bs,data.frame(x=npeak$RT/60)),col=2,lwd=2)
npeakRT<-npeak$RT/60
p3 <- ggplot(data =npeak,aes(x=npeakRT,y=npeak$intensity))+ geom_point()+
geom_smooth(method = "loess",se=F)+theme_light()+
geom_ribbon(aes(ymin=0,ymax=predict(loess(npeak$intensity~npeakRT))),fill="#00BFC4",alpha = 0.5)+
theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Smooth:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
ggsave(plot,filename=paste(i,"Smooth.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
#
diff<-diff(npeak$`m/z`)*100
pdf(file=paste(i,"Scan.pdf",sep=""))
plot(diff,type="h",xlab="Scan",ylab="m/z difference",cex.lab=1.5,lwd=5,col="cyan3",panel.first=grid(lty=1))
abline(h=mean(diff),col="#3366FF",lwd=3, lty=2)
abline(h=0,col="black")
title(main=paste("QC m/z scan:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
dev.off()
}
}else{
if (is.numeric(peakID) == FALSE) {
for (i in fullms$annotation$PeakID){
peak <- fullms$RawData2[which(fullms$RawData2[,7] == i), ]
peak<-as.data.frame(peak)
npeak<-peak[order(peak$RT),]
p3 <- ggplot(data =npeak,aes(npeak$RT/60 ,y=npeak$intensity))+
geom_area(data=npeak,aes(x=npeak$RT/60,y=npeak$intensity),fill="#00BFC4",alpha = 0.5,color="darkcyan")
p3b<-p3+theme_light()+theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3b+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Raw:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
ggsave(plot,filename=paste(i,"Raw.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
npeak<-as.data.frame(npeak)
# predict<-cbind(npeak,predict(fit))
#fit.bs<-lm(npeak$intensity~ bs(npeak$RT/60))
#lines(npeak$RT/60,predict(fit.bs,data.frame(x=npeak$RT/60)),col=2,lwd=2)
npeakRT<-npeak$RT/60
p3 <- ggplot(data =npeak,aes(x=npeakRT,y=npeak$intensity))+ geom_point()+
geom_smooth(method = "loess",se=F)+theme_light()+
geom_ribbon(aes(ymin=0,ymax=predict(loess(npeak$intensity~npeakRT))),fill="#00BFC4",alpha = 0.5)+
theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Smooth:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
ggsave(plot,filename=paste(i,"Smooth.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
#
diff<-diff(npeak$`m/z`)*100
pdf(file=paste(i,"Scan.pdf",sep=""))
plot(diff,type="h",xlab="Scan",ylab="m/z difference",cex.lab=1.5,lwd=5,col="cyan3",panel.first=grid(lty=1))
abline(h=mean(diff),col="#3366FF",lwd=3, lty=2)
abline(h=0,col="black")
title(main=paste("QC m/z scan:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
dev.off()
}}
else {
i=peakID
peak <- fullms$RawData2[which(fullms$RawData2[,7] == i), ]
peak<-as.data.frame(peak)
npeak<-peak[order(peak$RT),]
npeakRT<-npeak$RT/60
p3 <- ggplot(data =npeak,aes(npeak$RT/60 ,y=npeak$intensity))+
geom_area(data=npeak,aes(x=npeak$RT/60,y=npeak$intensity),fill="#00BFC4",alpha = 0.5,color="darkcyan")
p3b<-p3+theme_light()+theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3b+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Raw:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
ggsave(plot,filename=paste(i,"Raw.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
plot
npeak<-as.data.frame(npeak)
#predict<-cbind(npeak,predict(fit))
#fit.bs<-lm(npeak$intensity~ bs(npeak$RT/60))
#lines(npeak$RT/60,predict(fit.bs,data.frame(x=npeak$RT/60)),col=2,lwd=2)
npeakRT<-npeak$RT/60
p3 <- ggplot(data =npeak,aes(x=npeakRT,y=npeak$intensity))+ geom_point()+
geom_smooth(method = "loess",se=F)+theme_light()+
geom_ribbon(aes(ymin=0,ymax=predict(loess(npeak$intensity~npeakRT))),fill="#00BFC4",alpha = 0.5)+
theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Smooth:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
ggsave(plot,filename=paste(i,"Smooth.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
#
diff<-diff(npeak$`m/z`)*100
pdf(file=paste(i,"Scan.pdf",sep=""))
plot(diff,type="h",xlab="Scan",ylab="m/z difference",cex.lab=1.5,lwd=5,col="cyan3",panel.first=grid(lty=1))
abline(h=mean(diff),col="#3366FF",lwd=3, lty=2)
abline(h=0,col="black")
title(main=paste("QC m/z scan:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
dev.off()
}
}}}
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Defines functions plot_EIC
Documented in plot_EIC
plot_EIC<-function(fullms,peakID=333,ms=1,CE=0){
if(ms==1){
if (is.numeric(peakID) == FALSE) {
for (i in fullms$ms$peakID){
peak <- fullms$RawData1[which(fullms$RawData1[,7] == i), ]
peak<-as.data.frame(peak)
npeak<-peak[order(peak$RT),]
p3 <- ggplot(data =npeak,aes(npeak$RT/60 ,y=npeak$intensity))+
geom_area(data=npeak,aes(x=npeak$RT/60,y=npeak$intensity),fill="#00BFC4",alpha = 0.5,color="darkcyan")
p3b<-p3+theme_light()+theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3b+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Raw:",fullms$ms$name[fullms$ms$peakID==i]))
ggsave(plot,filename=paste(i,"Raw.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
npeak<-as.data.frame(npeak)
# predict<-cbind(npeak,predict(fit))
#fit.bs<-lm(npeak$intensity~ bs(npeak$RT/60))
#lines(npeak$RT/60,predict(fit.bs,data.frame(x=npeak$RT/60)),col=2,lwd=2)
npeakRT<-npeak$RT/60
p3 <- ggplot(data =npeak,aes(x=npeakRT,y=npeak$intensity))+ geom_point()+
geom_smooth(method = "loess",se=F)+theme_light()+
geom_ribbon(aes(ymin=0,ymax=predict(loess(npeak$intensity~npeakRT))),fill="#00BFC4",alpha = 0.5)+
theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Smooth:",fullms$ms$name[fullms$ms$peakID==i]))
ggsave(plot,filename=paste(i,"Smooth.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
diff<-diff(npeak$`m/z`)*100
tiff(filename=paste(i,"Scan.pdf",sep=""), res = 800, width = 6, height = 4, units = 'in')
plot(diff,type="h",xlab="Scan",ylab="m/z difference",cex.lab=1.5,lwd=5,col="cyan3",panel.first=grid(lty=1))
abline(h=mean(diff),col="#3366FF",lwd=3, lty=2)
abline(h=0,col="black")
title(main=paste("QC m/z scan:",fullms$ms$name[fullms$ms$peakID==i]))
dev.off()
}}else {
i=peakID
peak <- fullms$RawData[which(fullms$RawData[,7] == i), ]
peak<-as.data.frame(peak)
npeak<-peak[order(peak$RT),]
npeakRT<-npeak$RT/60
p3 <- ggplot(data =npeak,aes(npeak$RT/60 ,y=npeak$intensity))+
geom_area(data=npeak,aes(x=npeak$RT/60,y=npeak$intensity),fill="#00BFC4",alpha = 0.5,color="darkcyan")
p3b<-p3+theme_light()+theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3b+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Raw:",fullms$ms$name[fullms$ms$peakID==i]))
ggsave(plot,filename=paste(i,"Raw.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
p3 <- ggplot(data =npeak,aes(x=npeakRT,y=npeak$intensity))+ geom_point()+
geom_smooth(method = "loess",se=F)+theme_light()+
geom_ribbon(aes(ymin=0,ymax=predict(loess(npeak$intensity~npeakRT))),fill="#00BFC4",alpha = 0.5)+
theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Smooth:",fullms$ms$name[fullms$ms$peakID==i]))
ggsave(plot,filename=paste(i,"Smooth.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
diff<-diff(npeak$`m/z`)*100
tiff(filename=paste(i,"Scan.tiff",sep=""), res = 800, width = 6, height = 4, units = 'in')
plot(diff,type="h",xlab="Scan",ylab="m/z difference",cex.lab=1.5,lwd=5,col="cyan3",panel.first=grid(lty=1))
abline(h=mean(diff),col="#3366FF",lwd=3, lty=2)
abline(h=0,col="black")
title(main=paste("QC m/z scan:",fullms$ms$name[fullms$ms$peakID==i]))
dev.off()
}}else{
if(CE==0){
## here is for ms1 from DIA experiment
if (is.numeric(peakID) == FALSE) {
for (i in fullms$annotation$PeakID){
peak <- fullms$RawData1[which(fullms$RawData1[,7] == i), ]
peak<-as.data.frame(peak)
npeak<-peak[order(peak$RT),]
p3 <- ggplot(data =npeak,aes(npeak$RT/60 ,y=npeak$intensity))+
geom_area(data=npeak,aes(x=npeak$RT/60,y=npeak$intensity),fill="#00BFC4",alpha = 0.5,color="darkcyan")
p3b<-p3+theme_light()+theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3b+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Raw:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
ggsave(plot,filename=paste(i,"Raw.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
npeak<-as.data.frame(npeak)
# predict<-cbind(npeak,predict(fit))
#fit.bs<-lm(npeak$intensity~ bs(npeak$RT/60))
#lines(npeak$RT/60,predict(fit.bs,data.frame(x=npeak$RT/60)),col=2,lwd=2)
npeakRT<-npeak$RT/60
p3 <- ggplot(data =npeak,aes(x=npeakRT,y=npeak$intensity))+ geom_point()+
geom_smooth(method = "loess",se=F)+theme_light()+
geom_ribbon(aes(ymin=0,ymax=predict(loess(npeak$intensity~npeakRT))),fill="#00BFC4",alpha = 0.5)+
theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Smooth:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
ggsave(plot,filename=paste(i,"Smooth.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
#
diff<-diff(npeak$`m/z`)*100
pdf(file=paste(i,"Scan.pdf",sep=""))
plot(diff,type="h",xlab="Scan",ylab="m/z difference",cex.lab=1.5,lwd=5,col="cyan3",panel.first=grid(lty=1))
abline(h=mean(diff),col="#3366FF",lwd=3, lty=2)
abline(h=0,col="black")
title(main=paste("QC m/z scan:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
dev.off()
}}
else {
i=peakID
peak <- fullms$RawData1[which(fullms$RawData1[,7] == i), ]
peak<-as.data.frame(peak)
npeak<-peak[order(peak$RT),]
npeakRT<-npeak$RT/60
p3 <- ggplot(data =npeak,aes(npeak$RT/60 ,y=npeak$intensity))+
geom_area(data=npeak,aes(x=npeak$RT/60,y=npeak$intensity),fill="#00BFC4",alpha = 0.5,color="darkcyan")
p3b<-p3+theme_light()+theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3b+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Raw:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
ggsave(plot,filename=paste(i,"Raw.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
npeak<-as.data.frame(npeak)
#predict<-cbind(npeak,predict(fit))
#fit.bs<-lm(npeak$intensity~ bs(npeak$RT/60))
#lines(npeak$RT/60,predict(fit.bs,data.frame(x=npeak$RT/60)),col=2,lwd=2)
npeakRT<-npeak$RT/60
p3 <- ggplot(data =npeak,aes(x=npeakRT,y=npeak$intensity))+ geom_point()+
geom_smooth(method = "loess",se=F)+theme_light()+
geom_ribbon(aes(ymin=0,ymax=predict(loess(npeak$intensity~npeakRT))),fill="#00BFC4",alpha = 0.5)+
theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Smooth:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
ggsave(plot,filename=paste(i,"Smooth.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
#
diff<-diff(npeak$`m/z`)*100
pdf(file=paste(i,"Scan.pdf",sep=""))
plot(diff,type="h",xlab="Scan",ylab="m/z difference",cex.lab=1.5,lwd=5,col="cyan3",panel.first=grid(lty=1))
abline(h=mean(diff),col="#3366FF",lwd=3, lty=2)
abline(h=0,col="black")
title(main=paste("QC m/z scan:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
dev.off()
}
}else{
if (is.numeric(peakID) == FALSE) {
for (i in fullms$annotation$PeakID){
peak <- fullms$RawData2[which(fullms$RawData2[,7] == i), ]
peak<-as.data.frame(peak)
npeak<-peak[order(peak$RT),]
p3 <- ggplot(data =npeak,aes(npeak$RT/60 ,y=npeak$intensity))+
geom_area(data=npeak,aes(x=npeak$RT/60,y=npeak$intensity),fill="#00BFC4",alpha = 0.5,color="darkcyan")
p3b<-p3+theme_light()+theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3b+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Raw:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
ggsave(plot,filename=paste(i,"Raw.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
npeak<-as.data.frame(npeak)
# predict<-cbind(npeak,predict(fit))
#fit.bs<-lm(npeak$intensity~ bs(npeak$RT/60))
#lines(npeak$RT/60,predict(fit.bs,data.frame(x=npeak$RT/60)),col=2,lwd=2)
npeakRT<-npeak$RT/60
p3 <- ggplot(data =npeak,aes(x=npeakRT,y=npeak$intensity))+ geom_point()+
geom_smooth(method = "loess",se=F)+theme_light()+
geom_ribbon(aes(ymin=0,ymax=predict(loess(npeak$intensity~npeakRT))),fill="#00BFC4",alpha = 0.5)+
theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Smooth:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
ggsave(plot,filename=paste(i,"Smooth.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
#
diff<-diff(npeak$`m/z`)*100
pdf(file=paste(i,"Scan.pdf",sep=""))
plot(diff,type="h",xlab="Scan",ylab="m/z difference",cex.lab=1.5,lwd=5,col="cyan3",panel.first=grid(lty=1))
abline(h=mean(diff),col="#3366FF",lwd=3, lty=2)
abline(h=0,col="black")
title(main=paste("QC m/z scan:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
dev.off()
}}
else {
i=peakID
peak <- fullms$RawData2[which(fullms$RawData2[,7] == i), ]
peak<-as.data.frame(peak)
npeak<-peak[order(peak$RT),]
npeakRT<-npeak$RT/60
p3 <- ggplot(data =npeak,aes(npeak$RT/60 ,y=npeak$intensity))+
geom_area(data=npeak,aes(x=npeak$RT/60,y=npeak$intensity),fill="#00BFC4",alpha = 0.5,color="darkcyan")
p3b<-p3+theme_light()+theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3b+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Raw:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
ggsave(plot,filename=paste(i,"Raw.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
plot
npeak<-as.data.frame(npeak)
#predict<-cbind(npeak,predict(fit))
#fit.bs<-lm(npeak$intensity~ bs(npeak$RT/60))
#lines(npeak$RT/60,predict(fit.bs,data.frame(x=npeak$RT/60)),col=2,lwd=2)
npeakRT<-npeak$RT/60
p3 <- ggplot(data =npeak,aes(x=npeakRT,y=npeak$intensity))+ geom_point()+
geom_smooth(method = "loess",se=F)+theme_light()+
geom_ribbon(aes(ymin=0,ymax=predict(loess(npeak$intensity~npeakRT))),fill="#00BFC4",alpha = 0.5)+
theme(axis.text.x=element_text(size=12),axis.text.y=element_text(size=12),axis.title.x=element_text(size=16),axis.title.y = element_text(size=16,margin=margin(t=0,r=20,b=60,l=0)))
plot<-p3+ scale_x_continuous(name="Retention time (min)")+ scale_y_continuous(name="Intensity",labels= scales::scientific)+
ggtitle(paste("Smooth:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
ggsave(plot,filename=paste(i,"Smooth.tiff",sep=""), dpi = 800, width = 6, height = 4, units = 'in')
#
diff<-diff(npeak$`m/z`)*100
pdf(file=paste(i,"Scan.pdf",sep=""))
plot(diff,type="h",xlab="Scan",ylab="m/z difference",cex.lab=1.5,lwd=5,col="cyan3",panel.first=grid(lty=1))
abline(h=mean(diff),col="#3366FF",lwd=3, lty=2)
abline(h=0,col="black")
title(main=paste("QC m/z scan:",fullms$annotation$Metabolite[fullms$annotation$PeakID==i]))
dev.off()
}
}}}
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