makeReversible: Find reversible mutation matrix

In thoree/mut2: Reversible mutation matrices and pairwise likelihood ratios

Find reversible mutation matrix

Description

The Metropolis - Hastings algorithm is used to convert a mutation matrix to a reversible one, i.e., find the balanced matrix matrix.

Usage

makeReversible(mutmat, method = "MH", afreq = NULL, check = TRUE)

Arguments

mutmat	A mutation matrix.
method	Character. MH, PM or BA conversions.
afreq	A vector with allele frequencies of the same length as the size of mutmat.
check	Logical.

Details

Three different approaches are implemented. The default, method = "MH", gives a balanced matrix with off diagonal elements

q_{ij} min(1, p_j/p_i * q_{ji}/q_{ij})

where q_{ij} and p_i are the elements of the original mutation matrix and the allele frequencies, respectively. The average method method = "PM", gives a balanced matrix with off diagonal elements

(p_i q_{ij} + p_j q_{ji} ) / (2p_i)

if q_{ji} < p_i, i neq j (and may otherwise fail to balance).

The method Barker method = "BA", gives a balanced matrix with off diagonal elements

p_j q_{ji}/(p_i q_{ij} + p_j q_{ji})

If q_{ij} = 0 or q_{ji} = 0, the elements (i,j) and (j,i) of the transformed matrix becomes 0.

Value

Balanced mutation matrix. The expected mutation rate of the balanced matrix is returned as 'rate'.

Author(s)

Thore Egeland

Examples

library(pedmut)
n = 4
p = 1:n/sum(1:n)
names(p) = 1:n
mutmat = mutationMatrix("onestep", rate = 0.02, afreq = p, alleles = 1:n)
makeReversible(mutmat)
makeReversible(mutmat, method = "PM")
makeReversible(mutmat, method = "BA")

Q = matrix(ncol = 2, c(0.9,0.9, 0.1, 0.1))
p = c(0.01, 0.99)
mutmat = mutationMatrix("custom", matrix = Q, alleles = 1:2)
makeReversible(mutmat, afreq = p)
# PM balancing not possible:
# makeReversible(mutmat, method = "PM", afreq = p)

thoree/mut2 documentation built on May 16, 2023, 7:56 p.m.