dot-genetic_algorithm: Run the genetic-algorithm active subnetwork search

In pathfindR: Enrichment Analysis Utilizing Active Subnetworks

Run the genetic-algorithm active subnetwork search

Description

The initial population is seeded randomly (each gene switched on with probability params$gene_init_prob); when params$start_with_all_positives is set, one individual containing all positive-z-score nodes is added. The population then evolves by rank-based selection, uniform crossover and optional mutation. Every ten generations the worst 10% of the population is replaced with fresh random individuals, and the previous best individual is preserved. The search stops after params$ga_iterations generations or once the best individual is unchanged for 50 generations.

Usage

.genetic_algorithm(network, sc, params, verbose = FALSE)

Arguments

network	A network from build_network().
sc	A score context from build_score_context().
params	A list of run parameters.
verbose	Logical; emit progress messages.

Value

A list of subnetwork objects from the best individual found.

pathfindR documentation built on July 2, 2026, 1:06 a.m.