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