parameter: on object created by initializeParameterObject
gene.index: a integer or vector of integers representing the gene(s) of interesst.
samples: number of samples for the posterior estimate
Returns
returns a vector with the mixture assignment of each gene corresbonding to gene.index in the same order as the genome.
Details
The returned vector is unnamed as gene ids are only stored in the genome object, but the gene.index vector can be used to match the assignment to the genome.
Examples
genome_file <- system.file("extdata","genome.fasta", package ="AnaCoDa")genome <- initializeGenomeObject(file = genome_file)sphi_init <- c(1,1)numMixtures <-2geneAssignment <- c(rep(1,floor(length(genome)/2)),rep(2,ceiling(length(genome)/2)))parameter <- initializeParameterObject(genome = genome, sphi = sphi_init, num.mixtures = numMixtures, gene.assignment = geneAssignment, mixture.definition ="allUnique")model <- initializeModelObject(parameter = parameter, model ="ROC")samples <-2500thinning <-50adaptiveWidth <-25mcmc <- initializeMCMCObject(samples = samples, thinning = thinning, adaptive.width=adaptiveWidth, est.expression=TRUE, est.csp=TRUE, est.hyper=TRUE, est.mix =TRUE)divergence.iteration <-10## Not run:runMCMC(mcmc = mcmc, genome = genome, model = model, ncores =4, divergence.iteration = divergence.iteration)# get the mixture assignment for all genesmixAssign <- getMixtureAssignmentEstimate(parameter = parameter, gene.index =1:length(genome), samples =1000)# get the mixture assignment for a subsamplemixAssign <- getMixtureAssignmentEstimate(parameter = parameter, gene.index =5:100, samples =1000)# ormixAssign <- getMixtureAssignmentEstimate(parameter = parameter, gene.index = c(10,30:50,3,90), samples =1000)## End(Not run)