combine_loci: Combine the genotype frequencies and transition matrices of...

In clipp: Calculating Likelihoods by Pedigree Paring

Combine the genotype frequencies and transition matrices of two genetic loci

Description

A function to calculate the genotype frequencies and the transition matrices for the joint genotypes of two unlinked genetic loci in linkage equilibrium, given the corresponding objects for the separate loci. The results from this function can be used as inputs to pedigree_loglikelihood or genotype_probabilities to model the combined effect of the two loci on phenotypes.

Usage

combine_loci(geno_freq1, geno_freq2, trans1, trans2, annotate = FALSE)

Arguments

geno_freq1	A vector of strictly positive numbers that sum to 1, with geno_freq1[i] interpreted as the population genotype frequency of the ith possible genotype at a genetic locus (locus 1). When annotate is TRUE, the names of the genotypes at locus 1 will be taken to be names(geno_freq1) or, if names(geno_freq1) is NULL, to be 1:length(geno_freq1).
geno_freq2	Similar to geno_freq1 (above) but interpreted as the population genotype frequencies for a different genetic locus (locus 2).
trans1	An ngeno1^2 by ngeno1 matrix of non-negative numbers whose rows sum to 1, where ngeno1 = length(geno_freq1). This matrix is usually generated by trans_monogenic or a similar helper function, and its elements are interpreted as genetic transmission probabilities for locus 1 (see trans_monogenic for more details). If trans1 has ngeno1 + 2 instead of ngeno1 columns, as could occur if it was generated by trans_monogenic with annotate = TRUE, then the first two columns will be deleted and trans1 will be converted to a matrix.
trans2	Similar to trans1 (above) but interpreted as the genetic transmission probabilities for locus 2.
annotate	A logical flag. When FALSE (the default), the function returns objects that can be used as the geno_freq and trans arguments of pedigree_loglikelihood. When TRUE, the function annotates these objects (and converts trans to a data frame) to make the output more easily understood by humans.

Details

This function combines the genotype frequencies and transition probabilities of two unlinked genetic loci that are in linkage equilibrium in a given population. Because the loci are unlinked, any person's genotypes at the two loci are conditionally independent given his or her parental genotypes, and because the loci are in linkage equilibrium, the genotypes at the two loci for a random person from the population are independent. This function uses these assumptions to calculate the population frequencies and transition probabilities for the joint genotypes of the two loci, where a joint genotype is just a pair consisting of a genotype at locus 1 and a genotype at locus 2. If the annotate option is set to FALSE then these frequencies and probabilities can be used in pedigree_loglikelihood to model the combined effect of the two loci on the phenotypes. By a repeated application of this function, more than two genetic loci can be included in the genetic model.

Value

A list with the following components:

geno_freq	A vector of strictly positive numbers (the joint genotype frequencies) that sum to 1, with genotype names added when annotate is TRUE
trans	Either a matrix of genetic transmission probabilities suitable to be used as the trans argument of pedigree_loglikelihood (if annotate is FALSE), or a data frame that is an annotated version of this matrix (if annotate is TRUE).
genotype_decoder	A data frame giving the locus 1 and locus 2 genotypes that correspond to each joint genotype. In some cases, this could aid the user's calculation of the penet argument of pedigree_loglikelihood.

Examples

pa1 <- c(0.9, 0.1); names(pa1) <- c("-","+")
pa2 <- c(0.5, 0.5); names(pa2) <- c("A","a")
(geno_freq1 <- geno_freq_monogenic(pa1, TRUE))
(geno_freq2 <- geno_freq_monogenic(pa2, TRUE))
(trans1 <- trans_monogenic(2, TRUE))
(trans2 <- trans_monogenic(2))
(cl <- combine_loci(geno_freq1, geno_freq2, trans1, trans2, TRUE))
sum(cl$geno_freq)
apply(cl$trans[,-(1:2)], 1, sum)

clipp documentation built on July 12, 2022, 9:05 a.m.