optimDE: Optimizes enhancer model with evolutionary algorithm

In ndukler/superEnhancerModelR: superEnhancerModelR

Description

Runs differential evolution optimization method on enhancer model

Arguments

x	enhancerDataObject
maxit	the number of generations run (overrides the value set by control)
refine	if TRUE, run gradient descent on the best solution from the evolutionary algorithm
threads	integer value for number of threads to use (overrides the value set by control)
control	A list of control parameters that can be passed to DEoptim (also see DEoptim.control)

Examples

## Create a test design data.frame
design=expand.grid(E1=c(0,1),E2=c(0,1),E3=c(0,1))
## Create fake expression data
expression=c(0.001,0.2,0.3,0.7,0.4,0.8,0.6,1)*100
## Create activity function
actFun=formula(~E1+E2+E3+E1:E2)
edo = enhancerDataObject(expression,design,actFun)
edo=optimDE(edo,maxit=500,refine=TRUE)

ndukler/superEnhancerModelR documentation built on May 17, 2019, 8:18 p.m.