getMixtureAssignmentEstimate {AnaCoDa}

Returns mixture assignment estimates for each gene

Description

Posterior estimates for the mixture assignment of specified genes

Usage

getMixtureAssignmentEstimate(parameter, gene.index, samples)

Arguments

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

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.

Value

returns a vector with the mixture assignment of each gene corresbonding to gene.index in the same order as the genome.

Examples

 
genome_file <- system.file("extdata", "genome.fasta", package = "AnaCoDa")

genome <- initializeGenomeObject(file = genome_file)
sphi_init <- c(1,1)
numMixtures <- 2
geneAssignment <- 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 <- 2500
thinning <- 50
adaptiveWidth <- 25
mcmc <- 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 genes
mixAssign <- getMixtureAssignmentEstimate(parameter = parameter, 
                                          gene.index = 1:length(genome), samples = 1000)

# get the mixture assignment for a subsample
mixAssign <- getMixtureAssignmentEstimate(parameter = parameter, 
                                          gene.index = 5:100, samples = 1000)
# or
mixAssign <- getMixtureAssignmentEstimate(parameter = parameter, 
                                          gene.index = c(10, 30:50, 3, 90), samples = 1000)

## End(Not run)