getCSPEstimates function

Return Codon Specific Paramters (or write to csv) estimates as data.frame

getCSPEstimates returns the codon specific parameter estimates for a given parameter and mixture or write it to a csv file.

getCSPEstimates(
  parameter,
  filename = NULL,
  mixture = 1,
  samples = 10,
  relative.to.optimal.codon = T,
  report.original.ref = T,
  log.scale = F
)

Arguments

• parameter: parameter an object created by initializeParameterObject.
• filename: Posterior estimates will be written to file (format: csv). Filename will be in the format <parameter_name>_.csv.
• mixture: estimates for which mixture should be returned
• samples: The number of samples used for the posterior estimates.
• relative.to.optimal.codon: Boolean determining if parameters should be relative to the preferred codon or the alphabetically last codon (Default=TRUE). Only applies to ROC and FONSE models
• report.original.ref: Include the original reference codon (Default = TRUE). Note this is only included for the purposes of simulations, which expect the input parameter file to be in a specific format. Later version of AnaCoDa will remove this.
• log.scale: Calculate posterior means, standard deviation, and posterior probability intervals on the natural log scale. Should be used for PA and PANSE models only.

Returns

returns a list data.frame with the posterior estimates of the models codon specific parameters or writes it directly to a csv file if filename is specified

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)

## return estimates for codon specific parameters
csp_mat <- getCSPEstimates(parameter)

# write the result directly to the filesystem as a csv file. No values are returned
getCSPEstimates(parameter, filename=file.path(tempdir(), "test.csv"))
## End(Not run)