getExpressionEstimates function

Returns the estimated phi posterior for a gene

Posterior estimates for the phi value of specified genes

getExpressionEstimates(
  parameter,
  gene.index,
  samples,
  quantiles = c(0.025, 0.975),
  genome = NULL
)

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
• quantiles: vector of quantiles, (default: c(0.025, 0.975))
• genome: if genome is given, then will include gene ids in output (default is NULL)

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 <- 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 estimated expression values for all genes based on the mixture 
# they are assigned to at each step
estimatedExpression <- getExpressionEstimates(parameter, 1:length(genome), 1000)
## End(Not run)