[R] A better way to do this

[Dennis Murphy]

Hi:

Could you post a small, reproducible data set that illustrates what
you want to do? It sounds like you're creating 'spaghetti plots',
which can be done with a minimal amount of pain in ggplot2.

Dennis

On Thu, May 19, 2011 at 11:29 AM, 1Rnwb <sbpurohit at gmail.com> wrote:
> Hello gurus,
>
> I have a dataframe containing two groups viz., 'control' and 'case', each of
> these groups contains longitudinal data for 100 subjects. I have to plot all
> these subjects on a single chart and then put a regression line for each of
> the group for all the subjects. I have written a function to do the chart
> grpcharts<-function (dat, group,group2,molecule,cutoff){
> dat2<-dat[grep(group,dat$Group),]
> ylim=log2(c(min(dat2[,molecule],na.rm=T)+4,max(dat2[,molecule],na.rm=T)+1))
> all.sub.id<-dat2$Subject.ID
>  if (group=='control'){
>         col=c('blue')
> }else{col=c('red')}
>
> if(group2=='case'){
>        col2=c('red')
> }else{ col2=c('blue')}
> uniq.sub.id<-unique(all.sub.id)
>                 errcol<-c()
>                        for (i in 1: length(uniq.sub.id))
>                        {
>                         sub<-dat2[grep(uniq.sub.id[i],dat2$Subject.ID),]
>                         sub<- sub[order(sub$Age.at.Sample.Collection),]
>                         sub<-sub[sub[,molecule]>cutoff,]
>                         sub.id<-uniq.sub.id[i]
>                         if (dim(sub)[1]<=1) errcol<-c(errcol, sub.id)
>                         if (dim(sub)[1]>1)
>                                {
>                                 par(new=TRUE)
>                                 plot(log2(sub[,molecule])~sub$Age.at.Sample.Collection,
> ylab=paste('Log2_',molecule,sep=''),xlab="Age at Sample",pch=1, ylim=ylim,
> xlim=c(0,25),main=paste(group,'-',molecule))
>                                 mod<-loess(log2(sub[,molecule])~Age.at.Sample.Collection,
> na.action=na.exclude, data=sub)
>                                 pred<-predict(mod)
>                                 lines(pred~Age.at.Sample.Collection, data=sub,lwd=1, lty=1)
>                                 }
>                        }
>                   dat2<-dat2[order(dat2$Age.at.Sample.Collection),]
>                   mod<-loess(log2(dat2[,molecule])~Age.at.Sample.Collection,
> na.action=na.exclude, data=dat2)
>                   pred<-predict(mod)
>                   lines(pred~Age.at.Sample.Collection, data=dat2,lwd=2, lty=1,col=col)
>                   dat2<-dat[grep(group2,dat$Group),]
>                   dat2<-dat2[order(dat2$Age.at.Sample.Collection),]
>                   mod<-loess(log2(dat2[,molecule])~Age.at.Sample.Collection,
> na.action=na.exclude, data=dat2)
>                   pred<-predict(mod)
>                   lines(pred~Age.at.Sample.Collection, data=dat2,lwd=2, lty=1,col=col2)
>                   legend(c(20,20),c(ylim),c(group,group2), lty=1,lwd=2,col=c(col,col2),
> bty='n')
>                  print('done')
>        }
>
> the function subsets the data based on the 'group' and plots the datapoints
> currently I am using a loop to assign the colors under two conditions. I
> need some pointers to assign the colors to the regression lines for the two
> groups without using a loop.
> thanks
> sharad
>
>
> --
> View this message in context: http://r.789695.n4.nabble.com/A-better-way-to-do-this-tp3536576p3536576.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>