active_snw_enrichment_wrapper: Wrapper for Active Subnetwork Search + Enrichment over...
In pathfindR: Enrichment Analysis Utilizing Active Subnetworks

active_snw_enrichment_wrapper

R Documentation

Wrapper for Active Subnetwork Search + Enrichment over Single/Multiple Iteration(s)

Description

Wrapper for Active Subnetwork Search + Enrichment over Single/Multiple Iteration(s)

Usage

active_snw_enrichment_wrapper(
  input_processed,
  pin_path,
  gset_list,
  enrichment_threshold,
  list_active_snw_genes,
  adj_method = "bonferroni",
  search_method = "GR",
  disable_parallel = FALSE,
  use_all_positives = FALSE,
  iterations = 10,
  n_processes = NULL,
  score_quan_thr = 0.8,
  sig_gene_thr = 0.02,
  saTemp0 = 1,
  saTemp1 = 0.01,
  saIter = 10000,
  gaPop = 400,
  gaIter = 200,
  gaThread = 5,
  gaCrossover = 1,
  gaMut = 0,
  grMaxDepth = 1,
  grSearchDepth = 1,
  grOverlap = 0.5,
  grSubNum = 1000,
  silent_option = TRUE
)

Arguments

`input_processed`	processed input data frame
`pin_path`	path/to/PIN/file
`gset_list`	list for gene sets
`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`)
`adj_method`	correction method to be used for adjusting p-values. (default = 'bonferroni')
`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').
`disable_parallel`	boolean to indicate whether to disable parallel runs via `foreach` (default = FALSE)
`use_all_positives`	if TRUE: in GA, adds an individual with all positive nodes. In SA, initializes candidate solution with all positive nodes. (default = FALSE)
`iterations`	number of iterations for active subnetwork search and enrichment analyses (Default = 10)
`n_processes`	optional argument for specifying the number of processes used by foreach. If not specified, the function determines this automatically (Default == NULL. Gets set to 1 for Genetic Algorithm)
`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
`saTemp0`	Initial temperature for SA (default = 1.0)
`saTemp1`	Final temperature for SA (default = 0.01)
`saIter`	Iteration number for SA (default = 10000)
`gaPop`	Population size for GA (default = 400)
`gaIter`	Iteration number for GA (default = 200)
`gaThread`	Number of threads to be used in GA (default = 5)
`gaCrossover`	Applies crossover with the given probability in GA (default = 1, i.e. always perform crossover)
`gaMut`	For GA, applies mutation with given mutation rate (default = 0, i.e. mutation off)
`grMaxDepth`	Sets max depth in greedy search, 0 for no limit (default = 1)
`grSearchDepth`	Search depth in greedy search (default = 1)
`grOverlap`	Overlap threshold for results of greedy search (default = 0.5)
`grSubNum`	Number of subnetworks to be presented in the results (default = 1000)
`silent_option`	boolean value indicating whether to print the messages to the console (FALSE) or not (TRUE, this will print to a temp. file) during active subnetwork search (default = TRUE). This option was added because during parallel runs, the console messages get disorderly printed.