Linkage Disequilibrium
Compute Linkage Disequilibrium (LD) between given SNPs.
LD(x, lim, lim2, measure = c("r2", "r", "D"), trim = TRUE)x |
|
lim |
Range of SNPs for which the LD is computed |
lim2 |
(Optional) Second range of SNPs (see Details) |
measure |
The LD measure |
trim |
|
If lim2 is missing, the LD is computed between all SNPs with indices between lim[1] and lim[2];
else, the LD is computed between the SNPs in the range given by lim and those in the range given by lim2.
Note that the LD estimates are moment estimates (which are less precise than Maximum Likelihood Estimates).
If standardize(x) = "none", x will be standardized
using x@mu and x@sigma. If standardize(x) = "p", the moment estimates can produce r
values outside of the range [-1;1], hence the parameter trim. We recommend to set
standardize(x) <- "mu" (trimming can still be necessary due to rounding errors).
A matrix of LD values.
Hervé Perdry and Claire Dandine-Roulland
# Load data data(AGT) x <- as.bed.matrix(AGT.gen, AGT.fam, AGT.bim) # Compute LD ld.x <- LD(x, c(1,ncol(x))) # Plot a tiny part of the LD matrix LD.plot( ld.x[1:20,1:20], snp.positions = x@snps$pos[1:20] )
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