Here's a simple example that might help you get what you want:
set.seed(1)
x <- matrix(rnorm(30), ncol=3, dimnames=list(NULL, letters[1:3]))
(xc <- cor(x))
a b c
a 1.0000000 -0.3767034 -0.7158385
b -0.3767034 1.0000000 0.6040273
c -0.7158385 0.6040273 1.0000000
(cd <- data.frame(elt=outer(colnames(xc), colnames(xc), paste,
sep=":")[upper.tri(xc)], row=row(xc)[upper.tri(xc)], col=col(xc)[upper.tri(xc)],
cor=xc[upper.tri(xc)]))
elt row col cor
1 a:b 1 2 -0.3767034
2 a:c 1 3 -0.7158385
3 b:c 2 3 0.6040273
cd[order(-cd$cor),]
elt row col cor
3 b:c 2 3 0.6040273
1 a:b 1 2 -0.3767034
2 a:c 1 3 -0.7158385
If you need something more efficient, try using which(..., arr.ind) to pick out
matrix style indices, e.g.:
(ii <- which(xc > -0.4 & upper.tri(xc), arr.ind=T))
row col
a 1 2
b 2 3
cbind(ii, cor=xc[ii])
row col cor
a 1 2 -0.3767034
b 2 3 0.6040273
-- Tony Plate
Lee William wrote:
Hi! All,
I am working on a correlation matrix of 4217x4217 named 'cor_expN'. I wish
to obtain pairs with highest correlation values. So, I did this
b=matrix(data=NA,nrow=4217,ncol=1)
rownames(b)=rownames(cor_expN)
for(i in 1:4217){b[i,]=max(cor_expN[i,])}
head(b)
[,1]
aaeA_b3241_14 0.7181912
aaeB_b3240_15 0.7513084
aaeR_b3243_15 0.7681684
aaeX_b3242_12 0.5230587
aas_b2836_14 0.6615927
aat_b0885_14 0.6344144
Now I want the corresponding columns for the above values. For that I tried
this
c=matrix(data=NA,nrow=4217,ncol=1)
for(i in 1:4217){b[i,]=colnames(max(cor_expN[i,]))}
And got the following error:
Error in b[i, ] = colnames(max(cor_expN[i, ])) : number of items to replace
is not a multiple of replacement length
Any thoughts?
Lee
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