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.
