LD: Linkage Disequilibrium

In gaston: Genetic Data Handling (QC, GRM, LD, PCA) & Linear Mixed Models

Linkage Disequilibrium

Description

Compute Linkage Disequilibrium (LD) between given SNPs.

Usage

 LD(x, lim, lim2, measure = c("r2", "r", "D"), trim = TRUE) 

Arguments

x	A bed.matrix
lim	Range of SNPs for which the LD is computed
lim2	(Optional) Second range of SNPs (see Details)
measure	The LD measure
trim	Logical. If TRUE, the values above 1 or below -1 are replaced by 1 and -1 respectively.

Details

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).

Value

A matrix of LD values.

Author(s)

Hervé Perdry and Claire Dandine-Roulland

See Also

LD.thin, LD.plot

Examples

# 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] )

gaston documentation built on May 29, 2024, 7:33 a.m.