ISOpure.model_optimize.vv.vv_deriv_loglikelihood

<p>the column sums of log(theta), a 1xK matrix</p>

sum_log_theta

<p>Computes the derivative of the loglikelihood function relevant to optimizing vv for 
	step 1</p>

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.

Paul C. Boutros

ISOpureR

Deconvolution of Tumour Profiles

Gerald Quon 

Catalina V Anghel 

Syed Haider 

Francis Nguyen 

Amit G Deshwar 

Quaid D Morris 

Paul C Boutros 

ISOpure.model_optimize.vv.vv_deriv_loglikelihood function

Compute the derivative of the loglikelihood relevant to vv for step 1 — ISOpure.model_optimize.vv.vv_deriv_loglikelihood

Compute the derivative of the loglikelihood relevant to vv for step 1

ISOpure.model_optimize.vv.vv_deriv_loglikelihood: Compute the derivative of the loglikelihood relevant to vv for step 1

Description

Usage

Arguments

Value