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.
ISOpureS1.model_optimize.omega.omega_deriv_loglikelihood(ww, tumordata, model)(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
list containing all the parameters to be optimized
The negative derivative of the part of the loglikelihood function relevant to omega with respect to (log) omega