mcmc.bgx: Internal wrapper function for calling the bgx C++ function.
In bgx: Bayesian Gene eXpression

Description Usage Arguments Details Value Note Author(s) See Also

This internal function calls the bgx method in a loaded bgx shared object (bgx.so/bgx.dll)

mcmc.bgx(pm, mm, samplesets, probesets, numberCategories, categories, unknownProbeSeqs, numberOfUnknownProbeSeqs, 
  numberGenesToWatch, whichGenesToWatch, whichProbesToWatch, iter, burnin,
  adaptive, batch_size=50, optimalAR=0.44, output, samplenames = "unknown",
  subsample = ifelse(iter > 1024, iter/1024, 1), seed = 192492, rundir)

`pm`	Perfect Match probes
`mm`	MisMatch probes
`samplesets`	A numeric vector specifying which condition each array belongs to. E.g. if samplesets=c(2,2), then the first two replicates belong to one condition and the last two replicates belong to another condition. If NULL, each array is assumed to belong to a different condition.
`probesets`	A numeric vector specifying how probes are grouped into probesets.
`numberCategories`	Number of probe affinity categories.
`categories`	A numeric vector specifying which category each probe belongs to.
`unknownProbeSeqs`	A numeric vector specifying which probes lack sequence information.
`numberOfUnknownProbeSeqs`	Number of probes lacking sequence information.
`numberGenesToWatch`	How many genes to monitor closely.
`whichGenesToWatch`	A numeric vector specifying which genes to monitor closely.
`whichProbesToWatch`	The starting position for each probe in each gene to monitor closely.
`iter`	Number of post burn-in iterations.
`burnin`	Number of burn-in iterations.
`adaptive`	Use adaptive MCMC for better mixing.
`batch_size`	Batch size for adaptive MCMC.
`optimalAR`	Optimal acceptance ratio.
`output`	One of "minimal", "trace", "diagnostic" or "mcse".
`samplenames`	Vector of names for each array.
`subsample`	Subsampling interval.
`seed`	Seed for PRNG.
`rundir`	The directory in which to place the output run directories.