This function estimates the novel measure of linkage disequilibrium which is corrected by the structure of the sample.
Measure.R2S(biloci, struc, na.presence=TRUE)The returned value is the estimated value of the measure of linkage disequilibrium corrected by the structure of the sample or NA if less than 5 individuals have non-missing data at both loci.
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.
Numeric matrix (N x (P-1)), where N is the number of genotypes (or haplotypes) and P the number of sub-populations.
Matrix values are the probabilities for each genotypes (or haplotypes) to belong to each sub-populations.
Row names must correspond to the ID of individuals and must be ranged as in the biloci matrix.
Column names correspond to the ID of sub-populations.
The matrix must be inversible, if the structure is with P sub-populations, only P-1 columns are expected.
No missing value.
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.
David Desrousseaux, Florian Sandron, Aurélie Siberchicot, Christine Cierco-Ayrolles and Brigitte Mangin
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
data(data.test)
Geno <- data.test[[1]]
S.2POP <- data.test[[3]]
Measure.R2S(Geno, S.2POP)
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