R/ISOpureS2.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: ISOpureS2.model_optimize.kappa.kappa_compute_loglikelihood.R #######################################################
#
# Input variables:
#   kappa: a 1xK vector strength parameter in the prior over the cc given the cancer profile mm  
#   model: list containing all the parameters to be optimized
# 
# Output variables:
#    loglikelihood: computes the part of the likelihood function relevant to optimizing kappa
# 
# REVISIT: This function is not used in step 2, so the vectorisation has not been tested

ISOpureS2.model_optimize.kappa.kappa_compute_loglikelihood <- function(kappa, model) {
	
	omegaPP <- model$omega %*% model$PPtranspose; # size (D x G)
	kappaomegaPP <- omegaPP * ISOpure.util.repmat(t(kappa), 1, ncol(model$PPtranspose));  

	# D = number of tumour samples/patients
	D <- nrow(model$log_cc);

	loglikelihood <- 0;

	# loglikelihood calculation
	for (dd in 1:D) {
		loglikelihood <- loglikelihood + lgamma(sum(kappaomegaPP[dd,])) - sum(lgamma(kappaomegaPP[dd,])) + ((kappaomegaPP[dd,]-1) %*% (model$log_cc[dd,]));
	}

	return(loglikelihood);
}