ISOpureS1.model_optimize.omega.omega_deriv_loglikelihood

(K-1)x1 matrix, log(omega), where the entries in omega are constrained to add to 1
		where K-1 is the number of normal samples

a GxD matrix representing gene expression profiles of tumor samples

tumordata

list containing all the parameters to be optimized

model

Compute the derivative of the part of the loglikelihood function relevant to omega 
	with respect to (log) omega, in step 1. Instead of performing constrained optimization on omega 
	directly, we optimize the log of omega in an unconstrained fashion.

math

Deconvolution of mixed tumour profiles into normal and cancer for each patient, using
the ISOpure algorithm in Quon et al. Genome Medicine, 2013 5:29. Deconvolution requires
mixed tumour profiles and a set of unmatched "basis" normal profiles.

ISOpureS1.model_optimize.omega.omega_deriv_loglikelihood: Compute the derivative of loglikelihood relevant to omega for step 1

Description

Usage

Arguments

Value