Package: polySegratioMM 0.6-4

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_0.6-4.tar.gz
polySegratioMM_0.6-4.zip(r-4.5)polySegratioMM_0.6-4.zip(r-4.4)polySegratioMM_0.6-4.zip(r-4.3)
polySegratioMM_0.6-4.tgz(r-4.5-any)polySegratioMM_0.6-4.tgz(r-4.4-any)polySegratioMM_0.6-4.tgz(r-4.3-any)
polySegratioMM_0.6-4.tar.gz(r-4.5-noble)polySegratioMM_0.6-4.tar.gz(r-4.4-noble)
polySegratioMM_0.6-4.tgz(r-4.4-emscripten)polySegratioMM_0.6-4.tgz(r-4.3-emscripten)
polySegratioMM.pdf |polySegratioMM.html✨
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:

Conda:

4.08 score 24 scripts 165 downloads 26 exports 5 dependencies

Last updated 7 years agofrom:1ac4aa0dca. Checks:1 OK, 8 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 29 2025
R-4.5-winNOTEMar 29 2025
R-4.5-macNOTEMar 29 2025
R-4.5-linuxNOTEMar 29 2025
R-4.4-winNOTEMar 29 2025
R-4.4-macNOTEMar 29 2025
R-4.4-linuxNOTEMar 29 2025
R-4.3-winNOTEMar 29 2025
R-4.3-macNOTEMar 29 2025

Exports:calculateDICdiagnosticsJagsMixDistributionPlotBinomialDistributionPlotGammaDistributionPlotNormdosagesJagsMixdumpDatadumpInitsplot.runJagsWrapperplot.segratioMCMCplotFittedplotTheoreticalprint.dosagesMCMCprint.runJagsprint.runJagsWrapperprint.segratioMCMCreadJagsrunJagsrunSegratioMMsetControlsetInitssetModelsetPriorssummary.segratioMCMCwriteControlFilewriteJagsFile

Dependencies:codagdatagtoolslatticepolySegratio

polySegratioMM

Rendered frompolySegratioMM-overview.Rnwusingutils::Sweaveon Mar 29 2025.

Last update: 2018-03-23
Started: 2012-04-08

Readme and manuals

Help Manual

Help pageTopics
Bayesian Mixture Models for Marker Dosage in AutopolyploidspolySegratioMM-package polySegratioMM
Compute DIC for fitted mixture modelcalculateDIC
MCMC diagnostics for polyploid segregation ratio mixture modelsdiagnosticsJagsMix
Distribution PlotDistributionPlotBinomial DistributionPlotGamma DistributionPlotNorm
Compute dosages under specified Bayesian mixture modeldosagesJagsMix dosagesMCMC
Dumps segregation ratio data to file for subsequent JAGS rundumpData
Simulated autopolyploid dominant markers from 200 hexaploid individualshexmarkers
Simulated overdispersed autopolyploid dominant markers from 200 hexaploid individualshexmarkers.overdisp
Results of MCMC estimation for simulated overdispersed markersmcmcHexRun
MCMC plots for segregation ratio mixture modelsplot.segratioMCMC
Plot observed segregation ratios and fitted and theoretical modelsplot.runJagsWrapper plotFitted plotTheoretical
Doses from Bayesian mixture modelprint.dosagesMCMC print.segratioMCMC
Running JAGSprint.runJags print.runJagsWrapper
Read MCMC sample(s) from a JAGS runreadJags segratioMCMC
Run JAGS to create MCMC sample for segregation ratio mixture modelrunJags
Run a Bayesian mixture model for marker dosage with minimal effortrunJagsWrapper runSegratioMM
Set up controls for a JAGS segregation ratio model runsetControl
Set up and dump initial values given the model and priordumpInits setInits
Set characteristics of the Bayesian mixture model for dosagesmodelSegratioMM setModel
Set prior distributions for parameters of Bayesian mixture model for dosagessetPriors
Summary statistics for an segratioMCMC objectsummary.segratioMCMC summarySegratioMCMC
Write JAGS .cmd file for running JAGSwriteControlFile
Writes BUGS file for processing by JAGSwriteJagsFile