mat_pw_dps {graph4lg} | R Documentation |
Compute a pairwise genetic distance matrix between populations using Bowcock et al. (1994) formula
Description
The function computes the pairwise DPS, a genetic distance based on the proportion of shared alleles.
Usage
mat_pw_dps(x)
Arguments
x |
An object of class |
Details
The formula used is inspired from MSA software :
D_{PS}=1-\frac{\sum_{d}^{D}\sum_{k}^{K}\min (f_{a_{kd}i},f_{a_{kd}j})}{D}
such as a_{kd}
is the allele k
at locus d
D
is the total number of loci
K
is the allele number at each locus
\gamma_{a_{kd^{ij}}}=0
if individuals i
and j
do not share allele a_{kd}
\gamma_{a_{kd^{ij}}}=1
if one of individuals i
and j
has a copy of a_{kd}
\gamma_{a_{kd^{ij}}}=2
if both individuals have 2 copies
of a_{kd}
(homozygotes)
f_{a_{kd}i}
is allele a_{kd}
frequency in
individual i
(0, 0.5 or 1).
More information in :
Bowcock et al., 1994
and Microsatellite Analyser software (MSA) manual.
This function uses functions from adegenet package
Note that in the paper of Bowcock et al. (1994), the denominator is 2D.
But, in MSA software manual, the denominator is D.
Value
A pairwise matrix of genetic distances between populations
Author(s)
P. Savary
References
Bowcock AM, Ruiz-Linares A, Tomfohrde J, Minch E, Kidd JR, Cavalli-Sforza LL (1994). “High resolution of human evolutionary trees with polymorphic microsatellites.” nature, 368(6470), 455–457.
Examples
data("data_ex_genind")
dist_bowcock <- mat_pw_dps(data_ex_genind)