Active Subnetwork Search + Enrichment Analysis Wrapper for a Single Iteration

single_iter_wrapper(
  i = NULL,
  pin_path,
  network,
  experiment_df,
  score_quan_thr,
  sig_gene_thr,
  search_method,
  verbose,
  start_with_all_positives,
  gene_init_prob,
  sa_initial_temp,
  sa_final_temp,
  sa_iterations,
  ga_population_size,
  ga_iterations,
  ga_crossover_rate,
  ga_mutation_rate,
  gr_max_depth,
  gr_search_depth,
  gr_overlap_threshold,
  gr_subnetwork_num,
  gset_list,
  adj_method,
  enrichment_threshold,
  list_active_snw_genes
)

Arguments

i: current iteration index (default = NULL)
pin_path: path/to/PIN/file
network: Prebuilt network object as returned by build_network(), built once by active_snw_enrichment_wrapper and passed to every iteration to avoid redundant PIN file I/O.
experiment_df: input experiment data frame
score_quan_thr: active subnetwork score quantile threshold. Must be between 0 and 1 or set to -1 for not filtering. (Default = 0.8)
sig_gene_thr: threshold for the minimum proportion of significant genes in the subnetwork (Default = 0.02) If the number of genes to use as threshold is calculated to be < 2 (e.g. 50 signif. genes x 0.01 = 0.5), the threshold number is set to 2
search_method: algorithm to use when performing active subnetwork search. Options are greedy search (GR), simulated annealing (SA) or genetic algorithm (GA) for the search (default = 'GR').
verbose: boolean value indicating whether to print messages (default=FALSE)
start_with_all_positives: if TRUE: in GA, adds an individual with all positive nodes. In SA, initializes candidate solution with all positive nodes. (default = FALSE)
gene_init_prob: For SA and GA, probability of adding a gene in initial solution (default = 0.1)
sa_initial_temp: Initial temperature for SA (default = 1.0)
sa_final_temp: Final temperature for SA (default = 0.01)
sa_iterations: Iteration number for SA (default = 10000)
ga_population_size: Population size for GA (default = 400)
ga_iterations: Iteration number for GA (default = 200)
ga_crossover_rate: Applies crossover with the given probability in GA (default = 1, i.e. always perform crossover)
ga_mutation_rate: For GA, applies mutation with given mutation rate (default = 0, i.e. mutation off)
gr_max_depth: Sets max depth in greedy search, 0 for no limit (default = 1)
gr_search_depth: Search depth in greedy search (default = 1)
gr_overlap_threshold: Overlap threshold for results of greedy search (default = 0.5)
gr_subnetwork_num: Number of subnetworks to be presented in the results (default = 1000)
gset_list: list for gene sets.
adj_method: correction method to be used for adjusting p-values. (default = 'bonferroni')
enrichment_threshold: adjusted-p value threshold used when filtering enrichment results (default = 0.05)
list_active_snw_genes: boolean value indicating whether or not to report the non-significant active subnetwork genes for the active subnetwork which was enriched for the given term with the lowest p value (default = FALSE)

Value

Data frame of enrichment results using active subnetwork search results