Fits Bayesian mixture models to estimate marker dosage for dominant markers on autopolyploids using JAGS (1.0 or greater) as outlined in Baker et al (2010). May be used in conjunction with polySegratio for simulation studies and comparison with standard methods.
|Date of publication||2014-03-06 07:37:23|
|Maintainer||Peter Baker <firstname.lastname@example.org>|
calculateDIC: Compute DIC for fitted mixture model
diagnosticsJagsMix: MCMC diagnostics for polyploid segregation ratio mixture...
DistributionPlotBinomial: Distribution Plot
dosagesJagsMix: Compute dosages under specified Bayesian mixture model
dumpData: Dumps segregation ratio data to file for subsequent JAGS run
hexmarkers: Simulated autopolyploid dominant markers from 200 hexaploid...
hexmarkers.overdisp: Simulated overdispersed autopolyploid dominant markers from...
mcmcHexRun: Results of MCMC estimation for simulated overdispersed...
plotFitted: Plot observed segregation ratios and fitted and theoretical...
plot.segratioMCMC: MCMC plots for segregation ratio mixture models
polySegratioMM-package: Marker dosage for autoployploids by Bayesian mixture models
print.dosagesMCMC: Doses from Bayesian mixture model
print.runJags: Running JAGS
readJags: Read MCMC sample(s) from a JAGS run
runJags: Run JAGS to create MCMC sample for segregation ratio mixture...
runSegratioMM: Run a Bayesian mixture model for marker dosage with minimal...
setControl: Set up controls for a JAGS segregation ratio model run
setInits: Set up and dump initial values given the model and prior
setModel: Set characteristics of the Bayesian mixture model for dosages
setPriors: Set prior distributions for parameters of Bayesian mixture...
summary.segratioMCMC: Summary statistics for an segratioMCMC object
writeControlFile: Write JAGS .cmd file for running JAGS
writeJagsFile: Writes BUGS file for processing by JAGS