Package: polySegratioMM 0.6-5

polySegratioMM: Bayesian Mixture Models for Marker Dosage in Autopolyploids

Fits Bayesian mixture models to estimate marker dosage for dominant markers in autopolyploids using JAGS (1.0 or greater) as outlined in Baker et al "Bayesian estimation of marker dosage in sugarcane and other autopolyploids" (2010, <doi:10.1007/s00122-010-1283-z>). May be used in conjunction with polySegratio for simulation studies and comparison with standard methods.

Authors:Peter Baker [aut, cre]

polySegratioMM_0.6-5.tar.gz
polySegratioMM_0.6-5.zip(r-4.7-any)polySegratioMM_0.6-5.zip(r-4.6-any)polySegratioMM_0.6-5.zip(r-4.5-any)
polySegratioMM_0.6-5.tgz(r-4.6-any)polySegratioMM_0.6-5.tgz(r-4.5-any)
polySegratioMM_0.6-5.tar.gz(r-4.7-any)polySegratioMM_0.6-5.tar.gz(r-4.6-any)
polySegratioMM_0.6-5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
polySegratioMM/json (API)

# Install 'polySegratioMM' in R:

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

Bug tracker:https://github.com/petebaker/polysegratiomm/issues

Datasets:

hexmarkers - Simulated autopolyploid dominant markers from 200 hexaploid individuals
hexmarkers.overdisp - Simulated overdispersed autopolyploid dominant markers from 200 hexaploid individuals
mcmcHexRun - Results of MCMC estimation for simulated overdispersed markers

On CRAN:

4.11 score 26 scripts 331 downloads 26 exports 5 dependencies

Last updated from:d435c9d432. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	123
source / vignettes	OK	183
linux-release-x86_64	OK	125
macos-release-arm64	OK	140
macos-oldrel-arm64	OK	192
windows-devel	OK	74
windows-release	OK	81
windows-oldrel	OK	72
wasm-release	OK	120

Exports:calculateDIC diagnosticsJagsMix DistributionPlotBinomial DistributionPlotGamma DistributionPlotNorm dosagesJagsMix dumpData dumpInits plot.runJagsWrapper plot.segratioMCMC plotFitted plotTheoretical print.dosagesMCMC print.runJags print.runJagsWrapper print.segratioMCMC readJags runJags runSegratioMM setControl setInits setModel setPriors summary.segratioMCMC writeControlFile writeJagsFile

Dependencies:coda gdata gtools lattice polySegratio

polySegratioMM: An R library for Bayesian mixture models for marker dosage in autopolyploids

Simulated data | Fitting a mixture model | Assigning marker dosage | Acknowledgments | References

Rendered frompolySegratioMM-overview.Rmdusingknitr::rmarkdown

Last update: 2026-02-25
Started: 2026-02-25

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Bayesian Mixture Models for Marker Dosage in Autopolyploids	polySegratioMM-package polySegratioMM
Compute DIC for fitted mixture model	calculateDIC
MCMC diagnostics for polyploid segregation ratio mixture models	diagnosticsJagsMix
Distribution Plot	DistributionPlotBinomial DistributionPlotGamma DistributionPlotNorm
Compute dosages under specified Bayesian mixture model	dosagesJagsMix dosagesMCMC
Dumps segregation ratio data to file for subsequent JAGS run	dumpData
Simulated autopolyploid dominant markers from 200 hexaploid individuals	hexmarkers
Simulated overdispersed autopolyploid dominant markers from 200 hexaploid individuals	hexmarkers.overdisp
Results of MCMC estimation for simulated overdispersed markers	mcmcHexRun
MCMC plots for segregation ratio mixture models	plot.segratioMCMC
Plot observed segregation ratios and fitted and theoretical models	plot.runJagsWrapper plotFitted plotTheoretical
Doses from Bayesian mixture model	print.dosagesMCMC print.segratioMCMC
Running JAGS	print.runJags print.runJagsWrapper
Read MCMC sample(s) from a JAGS run	readJags segratioMCMC
Run JAGS to create MCMC sample for segregation ratio mixture model	runJags
Run a Bayesian mixture model for marker dosage with minimal effort	runJagsWrapper runSegratioMM
Set up controls for a JAGS segregation ratio model run	setControl
Set up and dump initial values given the model and prior	dumpInits setInits
Set characteristics of the Bayesian mixture model for dosages	modelSegratioMM setModel
Set prior distributions for parameters of Bayesian mixture model for dosages	setPriors
Summary statistics for an segratioMCMC object	summary.segratioMCMC summarySegratioMCMC
Write JAGS .cmd file for running JAGS	writeControlFile
Writes BUGS file for processing by JAGS	writeJagsFile