Measure.R2V: r^2_V measure

In LDcorSV: Linkage Disequilibrium Corrected by the Structure and the Relatedness

Description

This function estimates the novel measure of linkage disequilibrium which is corrected by the relatedness of genotyped individuals.

Usage

Measure.R2V(biloci, V, na.presence=TRUE, V_inv=NULL)

Arguments

biloci	Numeric matrix (N x 2), where N is the number of genotypes (or haplotypes). Matrix values are the allelic doses: - (0,1,2) for genotypes. - (0,1) for haplotypes. Row names correspond to the ID of individuals. Column names correspond to the ID of markers.
V	Numeric matrix (N x N), where N is the number of genotypes (or haplotypes). Matrix values are coefficients of genetic covariance for each pair of individuals. Rows and columns names must correspond to the ID of individuals and must be ranged in the same order as in the biloci matrix. No missing value.
na.presence	Boolean indicating the presence of missing values in data. If na.presence=FALSE (no missing data), computation of r^2_V and r^2_{VS} is largely optimized. By default, na.presence=TRUE.
V_inv	Should stay NULL.

Value

The returned value is the estimated value of the measure of linkage disequilibrium corrected by the relatedness of genotyped individuals or NA if less than 5 individuals have non-missing data at both loci.

Author(s)

David Desrousseaux, Florian Sandron, Aurélie Siberchicot, Christine Cierco-Ayrolles and Brigitte Mangin

References

Mangin, B., Siberchicot, A., Nicolas, S., Doligez, A., This, P., Cierco-Ayrolles, C. (2012). Novel measures of linkage disequilibrium that correct the bias due to population structure and relatedness. Heredity, 108 (3), 285-291. DOI: 10.1038/hdy.2011.73

Examples

data(data.test)
Geno <- data.test[[1]]
V.WAIS <- data.test[[2]]
Measure.R2V(Geno, V.WAIS)

Example output

[1] 0.1056732

LDcorSV documentation built on Aug. 26, 2020, 9:06 a.m.