And you might also consider packages like corrplot, corrgram etc. for other plotting options of a correlation matrix. They can be more informative than simply invoking image(heat)
> What a pleasant post to respond to - with self-contained code. :) > > heat<-matrix(0,nrow=dim(xa)[1],ncol=dim(xa)[2]) > > heat[lower.tri(heat)]<-xa[lower.tri(xa)] > heat[upper.tri(heat)]<-xb[upper.tri(xb)] > diag(heat)<-1 > > heat > > HTH, > Daniel > > > 1Rnwb wrote: >> >> Hello Gurus >> I have two correlation matrices 'xa' and 'xb' >> set.seed(100) >> d=cbind(x=rnorm(20)+1, >> x1=rnorm(20)+1, >> x2=rnorm(20)+1) >> >> >> d1=cbind(x=rnorm(20)+2, >> x1=rnorm(20)+2, >> x2=rnorm(20)+2) >> >> xa=cor(d,use='complete') >> >> xb=cor(d1,use='complete') >> >> >> >> I want to combine these two to get a third matrix which should have half >> values from 'xa' and half values from 'xb' >> x x1 x2 >> x 1.0000000 -0.15157123 -0.23085308 >> x1 0.3466155 1.00000000 -0.01061675 >> x2 0.1234507 0.01775527 1.00000000 >> >> I would like to generate a heatmap for correlation values in disease and >> non disease phenotype >> >> I would appreciate if someone can point me in correct direction. >> Thanks >> sharad >> > > -- > View this message in context: > http://r.789695.n4.nabble.com/correlation-matrix-tp3891085p3891685.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. > ______________________________________________ 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.
