LD {genetics}R Documentation

Pairwise linkage disequilibrium between genetic markers.

Description

Compute pairwise linkage disequilibrium between genetic markers

Usage

LD(g1, ...)
## S3 method for class 'genotype':
LD(g1,g2,...)
## S3 method for class 'data.frame':
LD(g1,...)

Arguments

g1 genotype object or dataframe containing genotype objects
g2 genotype object (ignored if g1 is a dataframe)
... optional arguments (ignored)

Details

Linkage disequilibrium (LD) is the non-random association of marker alleles and can arise from marker proximity or from selection bias.

LD.genotype estimates the extent of LD for a single pair of genotypes. LD.data.frame computes LD for all pairs of genotypes contained in a data frame. Before starting, LD.data.frame checks the class and number of alleles of each variable in the dataframe. If the data frame contains non-genotype objects or genotypes with more or less than 2 alleles, these will be omitted from the computation and a warning will be generated.

Three estimators of LD are computed:

where

For genotype data, AB/ab cannot be distinguished from aB/Ab. Consequently, we estimate p(AB) using maximum likelihood and use this value in the computations.

Value

LD.genotype returns a 5 element list:

call the matched call
D Linkage disequilibrium estimate
Dprime Scaled linkage disequilibrium estimate
corr Correlation coefficient
nobs Number of observations
chisq Chi-square statistic for linkage equilibrium (i.e., D=D'=corr=0)
p.value Chi-square p-value for marker independence


LD.data.frame returns a list with the same elements, but each element is a matrix where the upper off-diagonal elements contain the estimate for the corresponding pair of markers. The other matrix elements are NA.

Author(s)

Gregory R. Warnes warnes@bst.rochester.edu

See Also

genotype, HWE.test

Examples


g1 <- genotype( c('T/A',    NA, 'T/T',    NA, 'T/A',    NA, 'T/T', 'T/A',
                  'T/T', 'T/T', 'T/A', 'A/A', 'T/T', 'T/A', 'T/A', 'T/T',
                     NA, 'T/A', 'T/A',   NA) )

g2 <- genotype( c('C/A', 'C/A', 'C/C', 'C/A', 'C/C', 'C/A', 'C/A', 'C/A',
                  'C/A', 'C/C', 'C/A', 'A/A', 'C/A', 'A/A', 'C/A', 'C/C',
                  'C/A', 'C/A', 'C/A', 'A/A') )

g3 <- genotype( c('T/A', 'T/A', 'T/T', 'T/A', 'T/T', 'T/A', 'T/A', 'T/A',
                  'T/A', 'T/T', 'T/A', 'T/T', 'T/A', 'T/A', 'T/A', 'T/T',
                  'T/A', 'T/A', 'T/A', 'T/T') )

# Compute LD on a single pair

LD(g1,g2)

# Compute LD table for all 3 genotypes

data <- makeGenotypes(data.frame(g1,g2,g3))
LD(data)

[Package genetics version 1.3.4 Index]