Perform Active Subnetwork Search

active_snw_search(
input_for_search,
pin_name_path = "Biogrid",
snws_file = "active_snws",
dir_for_parallel_run = NULL,
score_quan_thr = 0.8,
sig_gene_thr = 0.02,
search_method = "GR",
silent_option = TRUE,
use_all_positives = FALSE,
geneInitProbs = 0.1,
saTemp0 = 1,
saTemp1 = 0.01,
saIter = 10000,
gaPop = 400,
gaIter = 10000,
gaCrossover = 1,
gaMut = 0,
grMaxDepth = 1,
grSearchDepth = 1,
grOverlap = 0.5,
grSubNum = 1000
)

## Arguments

input_for_search input the input data that active subnetwork search uses. The input must be a data frame containing at least these 2 columns: GENEGene Symbol P_VALUEp value obtained through a test, e.g. differential expression/methylation Name of the chosen PIN or path/to/PIN.sif. If PIN name, must be one of c("Biogrid", "STRING", "GeneMania", "IntAct", "KEGG", "mmu_STRING"). If path/to/PIN.sif, the file must comply with the PIN specifications. (Default = "Biogrid") name for active subnetwork search output data without file extension (default = "active_snws") (previously created) directory for a parallel run iteration. Used in the wrapper function (see ?run_pathfindR) (Default = NULL) active subnetwork score quantile threshold. Must be between 0 and 1 or set to -1 for not filtering. (Default = 0.8) 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 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"). 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. if TRUE: in GA, adds an individual with all positive nodes. In SA, initializes candidate solution with all positive nodes. (default = FALSE) For SA and GA, probability of adding a gene in initial solution (default = 0.1) Initial temperature for SA (default = 1.0) Final temperature for SA (default = 0.01) Iteration number for SA (default = 10000) Population size for GA (default = 400) Iteration number for GA (default = 200) Number of threads to be used in GA (default = 5) Applies crossover with the given probability in GA (default = 1, i.e. always perform crossover) For GA, applies mutation with given mutation rate (default = 0, i.e. mutation off) Sets max depth in greedy search, 0 for no limit (default = 1) Search depth in greedy search (default = 1) Overlap threshold for results of greedy search (default = 0.5) Number of subnetworks to be presented in the results (default = 1000)

## Value

A list of genes in every identified active subnetwork that has a score greater than the score_quan_thrth quantile and that has at least sig_gene_thr affected genes.

## Examples

processed_df <- RA_input[1:15, -2]
colnames(processed_df) <- c("GENE", "P_VALUE")
GR_snws <- active_snw_search(input_for_search = processed_df,
pin_name_path = "KEGG",
search_method = "GR",
score_quan_thr = 0.8)
#> Found 2 active subnetworks
#>
# clean-up