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MasterBayes (version 2.55)

ML and MCMC Methods for Pedigree Reconstruction and Analysis

Description

The primary aim of MasterBayes is to use MCMC techniques to integrate over uncertainty in pedigree configurations estimated from molecular markers and phenotypic data. 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.

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Version

Install

install.packages('MasterBayes')

Monthly Downloads

162

Version

2.55

License

GPL (>= 2)

Maintainer

Jarrod Hadfield

Last Published

July 29th, 2017

Functions in MasterBayes (2.55)

Maximum Likelihood Estimation of Beta

Maximum Likelihood Estimation of the Pedigree

GdataPed Object

Markov chain Monte Carlo Methods for Pedigree Reconstruction and Analysis

Seychelles Warbler Phenotypes

Autocorrelation Function for Parenatge Assignment

PdataPed Object

Seychelles Warbler Genotypes

Maximum Likelihood Estimation of the Unsampled Population Size

Maximum Likelihood and Markov chain Monte Carlo methods for Pedigree Reconstruction, Analysis and Simulation.

Genotype Objects for all Loci

genotypeD Object

Orders a Pedigree

Log-Likelihood of Unsampled Population Size

Log-Likelihood of Beta

Obtains a consensus genotype from duplicate samples

Reorders Design Matrices

Genotype and Genotyping Error Simulation

Legal Genotype Configurations

Parent-Offspring Genotype Mismatches

Returns pairs of individuals that fall into specific relatedness categories

priorPed Object

summary.genotypeD

genotypeD Object

Design Matrices for the Multinomial Log-Linear Model

Inserts Founders into a Pedigree

Posterior Mode of Genotypes

Posterior Mode of Parents

Allele Frequencies

Mendelian Transition Probabilities

Simulates a Pedigree given a Log-Linear Model

Transforms Variables for a Multinomial Log-Linear Model

startPed Object