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.
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. >
You may try "xyplot" 2011/5/20 1Rnwb <sbpurohit@gmail.com>> 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@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. >[[alternative HTML version deleted]]
here is the data set, yes i am doing spagghetti plots for each Subject for MCP1 with respect to the Age.at.Sample.Collection, with a final of all the controls and all the cases Subject.ID sample Group Age.at.Sample.Collection MCP1 19 00173-0 3455 control 11.767282 212.4438625 104 00173-0 4992 control 4.087611 222.6706897 148 00173-0 5046 control 5.103353 257.5997389 192 00173-0 5205 control 7.249828 191.8050229 223 00173-0 4991 control 6.061601 171.2995728 235 00173-0 5295 control 7.843942 240.2288223 275 00173-0 5366 control 9.817932 64.9237708 319 00173-0 5473 control 10.704996 199.4368169 2102 00173-0 3140 control 15.260780 366.1121484 3174 00173-0 4950 control 14.012320 253.4390051 3883 00173-0 4103 control 12.974674 260.3490578 23 01039-0 901388 control 3.058179 273.6916770 491 01039-0 901068 control 1.284052 255.5981436 735 01039-0 900985 control 1.968514 450.2616943 1199 01039-0 900733 control 5.086926 161.5011670 3948 01039-0 901422 control 4.041067 365.8560986 24 21038-0 901594 control 8.418891 303.9160091 128 21038-0 900089 control 12.440793 250.4846256 381 21038-0 901157 control 6.477754 35.3079462 486 21038-0 901739 control 6.669404 77.1044173 582 21038-0 900313 control 10.464065 233.8540385 972 21038-0 900527 control 11.438740 194.8173368 1256 21038-0 900262 control 14.472279 175.7577419 1565 21038-0 901475 control 2.015058 246.2465683 1641 21038-0 901216 control 4.416153 99.7496760 1957 21038-0 901618 control 6.669404 141.4459310 2291 21038-0 900563 control 3.025325 278.6264989 3131 21038-0 900363 control 5.470225 103.3293132 3704 21038-0 900872 control 9.434633 153.7875157 3984 21038-0 900766 control 13.437371 269.4589484 2 00041-0 3810 case 17.368925 203.1979716 310 00041-0 4923 case 17.648186 168.8229783 444 00041-0 3842 case 16.375085 102.6136126 1082 00041-0 4078 case 16.813141 89.7548225 1459 00041-0 5005 case 14.817248 131.0459201 1464 00041-0 4816 case 16.082135 131.1120569 1470 00041-0 3495 case 15.323750 118.7034216 1677 00041-0 3991 case 9.782340 169.1765831 1845 00041-0 4824 case 8.520191 122.3348897 1928 00041-0 4599 case 16.651608 2.3051960 2142 00041-0 3146 case 15.164955 191.6823727 2184 00041-0 3220 case 15.526351 188.6667153 2283 00041-0 5239 case 18.269678 174.9620952 2542 00041-0 3536 case 10.910335 301.6238182 2883 00041-0 4787 case 13.527720 159.0956166 2921 00041-0 4058 case 17.845311 137.7700442 2932 00041-0 5015 case 7.520876 101.6216590 3641 00041-0 4266 case 5.497604 125.6831543 3683 00041-0 4360 case 4.421629 187.2961108 3725 00041-0 4428 case 13.451060 157.4203222 3767 00041-0 4506 case 6.507871 141.1115853 3889 00041-0 4455 case 12.147843 213.7489685 3 00709-0 5023 case 2.004106 412.4962003 398 00709-0 3180 case 5.234770 9.6108457 639 00709-0 3205 case 4.974674 262.5951990 1058 00709-0 3788 case 4.577686 281.6220685 1700 00709-0 3450 case 4.156057 131.7354794 2050 00709-0 3183 case 5.878165 0.3707844 2483 00709-0 4434 case 2.162902 339.0410965 2789 00709-0 3849 case 4.405201 405.9685980 3281 00709-0 3619 case 5.541409 255.1460421 3842 00709-0 3943 case 3.515400 624.2636701 4011 00709-0 5304 case 3.312799 2.9206063 4 00174-0 4142 case 16.060232 240.4858235 13 00174-0 4244 case 5.615331 NA 22 00174-0 4446 case 15.523613 223.3748681 57 00174-0 4292 case 6.209445 168.6679707 100 00174-0 4314 case 6.666666 147.6358300 183 00174-0 3689 case 16.224503 0.5689179 270 00174-0 4208 case 3.468856 286.9223725 313 00174-0 4223 case 4.427104 178.0005964 471 00174-0 3188 case 11.633127 150.2065531 554 00174-0 3212 case 12.377823 217.9799114 1304 00174-0 5193 case 14.694045 150.0169015 1463 00174-0 4443 case 13.626283 155.9339661 1589 00174-0 5294 case 13.990417 167.2262451 1884 00174-0 4349 case 15.271731 146.8486102 1975 00174-0 3857 case 10.611909 82.6978002 2084 00174-0 3174 case 10.924024 217.8106656 2196 00174-0 5126 case 16.892539 272.8141490 2748 00174-0 4607 case 16.481861 156.5503087 2963 00174-0 4861 case 11.967145 294.4989050 3294 00174-0 4859 case 12.783025 205.6801413 3566 00174-0 4380 case 9.070499 84.6743348 3608 00174-0 4405 case 10.132785 92.1683089 3844 00174-0 4252 case 10.324435 305.3678248 3923 00174-0 4193 case 11.340177 336.7327758>-- View this message in context: http://r.789695.n4.nabble.com/A-better-way-to-do-this-tp3536576p3542376.html Sent from the R help mailing list archive at Nabble.com.