Package: MasterBayes 2.59

MasterBayes: Maximum Likelihood and Markov Chain Monte Carlo (MCMC) Methods for Pedigree Reconstruction and Analysis

The primary aim of 'MasterBayes' is to use Markov chain Monte Carlo (MCMC) techniques to integrate over uncertainty in pedigree configurations estimated from molecular markers and phenotypic data (Hadfield et al. (2006) <doi:10.1111/j.1365-294X.2006.03050.x>). Emphasis is put on the marginal distribution of parameters that relate the phenotypic data to the pedigree. All simulation is done in compiled 'C++' for efficiency.

Authors:Jarrod Hadfield [aut, cre], Andrew D. Martin [ctb, cph], Kevin M. Quinn [ctb, cph], Daniel Pemstein [ctb, cph]

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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
MasterBayes/json (API)

# Install 'MasterBayes' in R:

install.packages('MasterBayes', repos = c('https://jarrodhadfield.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jarrodhadfield/masterbayes/issues

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

WarblerG - Seychelles Warbler Genotypes
WarblerP - Seychelles Warbler Phenotypes

On CRAN:

cpp

4.83 score 67 scripts 682 downloads 25 mentions 35 exports 16 dependencies

Last updated from:489159e7e7. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	178
linux-devel-x86_64	OK	194
source / vignettes	OK	202
linux-release-arm64	OK	166
linux-release-x86_64	OK	197
macos-release-arm64	OK	157
macos-release-x86_64	OK	324
macos-oldrel-arm64	OK	114
macos-oldrel-x86_64	OK	365
windows-devel	OK	206
windows-release	OK	208
windows-oldrel	OK	198
wasm-release	OK	144

Exports:autocorrP beta.loglik consensusG extractA fillX.G GdataPed genotype.list genotypeD getXlist insertPed is.GdataPed is.genotypeD is.PdataPed is.priorPed is.startPed is.tunePed legalG MCMCped mismatches MLE.beta MLE.ped MLE.popsize modeG modeP orderPed PdataPed popsize.loglik post.pairs priorPed reordXlist simgenotypes simpedigree startPed tunePed varPed

Dependencies:coda combinat evaluate gdata genetics gtools highr kinship2 knitr lattice MASS Matrix mvtnorm quadprog xfun yaml

MasterBayes Tutorial

Rendered fromTutorial.Rnwusingutils::Sweave

Last update: 2020-06-22
Started: 2020-06-22

Help page	Topics
Autocorrelation Function for Parenatge Assignment	autocorrP
Log-Likelihood of Beta	beta.loglik
Obtains a consensus genotype from duplicate samples	consensusG
Allele Frequencies	extractA
Mendelian Transition Probabilities	fillX.G
GdataPed Object	GdataPed is.GdataPed
Genotype Objects for all Loci	genotype.list
genotypeD Object	genotypeD is.genotypeD
Design Matrices for the Multinomial Log-Linear Model	getXlist
Inserts Founders into a Pedigree	insertPed
Legal Genotype Configurations	legalG
Maximum Likelihood (ML) and Markov chain Monte Carlo (MCMC) methods for Pedigree Reconstruction, Analysis and Simulation.	MasterBayes
Markov chain Monte Carlo (MCMC) Methods for Pedigree Reconstruction and Analysis	MCMCped
Parent-Offspring Genotype Mismatches	mismatches
Maximum Likelihood Estimation of Beta	MLE.beta
Maximum Likelihood Estimation of the Pedigree	MLE.ped
Maximum Likelihood Estimation of the Unsampled Population Size	MLE.popsize
Posterior Mode of Genotypes	modeG
Posterior Mode of Parents	modeP
Orders a Pedigree	orderPed
PdataPed Object	is.PdataPed PdataPed
Log-Likelihood of Unsampled Population Size	popsize.loglik
Returns pairs of individuals that fall into specific relatedness categories	post.pairs
priorPed Object	is.priorPed priorPed
Reorders Design Matrices	reordXlist
Genotype and Genotyping Error Simulation	simgenotypes
Simulates a Pedigree given a Log-Linear Model	simpedigree
startPed Object	is.startPed startPed
genotypeD Object	summary summary.genotypeD
tunePed Object	is.tunePed tunePed
Transforms Variables for a Multinomial Log-Linear Model	varPed
Seychelles Warbler Genotypes	WarblerG
Seychelles Warbler Phenotypes	WarblerP

Package: MasterBayes 2.59

MasterBayes: Maximum Likelihood and Markov Chain Monte Carlo (MCMC) Methods for Pedigree Reconstruction and Analysis

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Usage by other packages (reverse dependencies)