R/ISOpureS1.model_optimize.kappa.kappa_compute_loglikelihood.R

In ISOpureR: Deconvolution of Tumour Profiles

# The ISOpureR package is copyright (c) 2014 Ontario Institute for Cancer Research (OICR)
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### FUNCTION: ISOpureS1.model_optimize.kappa.kappa_compute_loglikelihood.R #######################################################
#
# Input variables:
#   kappa: a scalar kappa, the strength parameter in the prior over the reference
#          cancer profile.  
#   tumordata: a GxD matrix representing gene expression profiles of tumour samples
#   model: list containing all the parameters to be optimized
# 
# Output variables:
#    loglikelihood: computes the part of the likelihood function relevant to optimizing kappa
#
# # REVISIT: 
# 1. This function is not vectorized, as FOR STEP 1 in Matlab, as kappa is a scalar.
#    May have to alter this for backwards compatibility with ISOLATE?

ISOpureS1.model_optimize.kappa.kappa_compute_loglikelihood <- function(kappa, tumordata, model) {
    
    kappa <- as.numeric(kappa);
    omega <- as.numeric(model$omega);
    kappaomegaPP <- as.numeric(kappa * t(model$omega) %*% model$PPtranspose); 
    
    loglikelihood <- lgamma(sum(kappaomegaPP)) - sum(lgamma(kappaomegaPP)) + ((kappaomegaPP-1) %*% (t(model$log_all_rates[nrow(model$log_all_rates), ,drop=FALSE])));
    return(loglikelihood);
}