Inference concerning equilibrium and random mating in autopolyploids. Methods are available to test for equilibrium and random mating at any even ploidy level (>2) in the presence of double reduction at biallelic loci. For autopolyploid populations in equilibrium, methods are available to estimate the degree of double reduction. We also provide functions to calculate genotype frequencies at equilibrium, or after one or several rounds of random mating, given rates of double reduction. For details of these methods, see Gerard (2022a) \<doi:10.1111/biom.13722> and Gerard (2022b) \<doi:10.1101/2022.08.11.503635>.
The main functions for inference are:
hwefit()
: Fit either hwelike()
,rmlike()
, hweustat()
,
hwenodr()
, or hweboot()
across many loci. Parallelization is
supported through the
future package.
hwelike()
: Likelihood inference for equilibrium. This function
estimates the rate of double reduction given equilibrium, and tests
for at most small deviations from equilibrium.
rmlike()
: Likelihood inference for random mating in polyploids. This
function tests for random mating and estimates gametic frequencies
given random mating. This function does not assume a model for
meiosis.
hweustat()
: U-statistic approach for equilibrium and double
reduction. This function tests for equilibrium given double reduction
rates and estimates these rates given equilibrium.
hwenodr()
: Implements a likelihood ratio test that tests for
Hardy-Weinberg equilibrium in autopolyploids given no double
reduction.
hweboot()
: Implements a bootstrap approach to test for equilibrium
which is more appropriate for small samples and uncertain genotypes.
rmbayes()
: Implements a Bayesian test for random mating in
autopolyploids for any ploidy level.
rmbayesgl()
: Bayesian test for random mating, accounting for
genotype uncertainty using genotype likelihoods.
menbayesgl()
: Bayesian test for Mendelian segregation frequencies in
S1 or F1 populations using genotype likelihoods.
Functions are provided for calculating genotype frequencies for individuals and gametes:
gsegmat()
: Produces the segregation probabilities for gamete dosages
given parental dosages and the double reduction rate.
gsegmat_symb()
: Provides a symbolic representation of the output of
gsegmat()
.
zsegarray()
: Obtains offspring genotype probabilities given parental
probabilities, the ploidy of the species, and the overdispersion
parameter, for all possible parental genotypes.
freqnext()
: Updates the genotype frequencies after one generation of
random mating.
hwefreq()
: Calculate genotype frequencies at equilibrium.
The bounds on the double reduction rate under the complete equational
segregation model are provided by drbounds()
.
Functions for evaluating the uniformity of p-values are provided in
ts_bands()
and qqpvalue()
.
You can install the released version of hwep from CRAN with:
install.packages("hwep")
You can install the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("dcgerard/hwep")
To cite hwep in publications use:
Gerard D (2022). “Double reduction estimation and equilibrium tests in natural autopolyploid populations.” Biometrics In press. doi:10.1111/biom.13722.
A BibTeX entry for LaTeX users is
@Article{,
title = {Double reduction estimation and equilibrium tests in natural autopolyploid populations},
author = {David Gerard},
journal = {Biometrics},
year = {2022},
doi = {10.1111/biom.13722},
volume = {In press},
}
If you use rmbayes()
, rmbayesgl()
, or menbayeslg()
, then please
also cite
Gerard D (2022). “Bayesian tests for random mating in autopolyploids.” bioRxiv. doi:10.1101/2022.08.11.503635.
A BibTeX entry for LaTeX users is
@article{,
author = {Gerard, David},
title = {Bayesian Tests for Random Mating in Autopolyploids},
year = {2022},
doi = {10.1101/2022.08.11.503635},
publisher = {Cold Spring Harbor Laboratory},
journal = {bioRxiv}
}
This material is based upon work supported by the National Science Foundation under Grant No. 2132247. The opinions, findings, and conclusions or recommendations expressed are those of the author and do not necessarily reflect the views of the National Science Foundation.
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