Find the subnetwork of significant edges connecting the genes.

Usage

BuildSubnetwork(
  geneSet,
  networks,
  alpha,
  hopConstraint,
  nullDistribution,
  verbose = FALSE,
  topX = NULL,
  doFDRAdjustment = TRUE,
  pValueChunks = 100,
  loadPValues = FALSE,
  pValueFile = "pvalues.RDS"
)

Arguments

geneSet: A character vector of genes comprising the targets of interest.
networks: A list of bipartite (PANDA-like) networks, where each network is a data frame with the following format: tf,gene,score
alpha: The significance cutoff for the statistical test.
hopConstraint: The maximum number of hops to be considered between gene pairs. Must be an even number.
nullDistribution: The null distribution, specified as a vector of values.
verbose: Whether or not to print detailed information about the run.
topX: Select the X lowest significant p-values for each gene. NULL by default.
doFDRAdjustment: Whether or not to perform FDR adjustment.
pValueChunks: The number of chunks to split when calculating the p-value. This parameter allows the edges to be split into chunks to prevent memory errors.
loadPValues: Whether p-values should be loaded from pValueFile or re-generated. Default is FALSE.
pValueFile: The file where the p-values should be saved. If NULL, they are not saved and need to be recalculated.

Value

A bipartite subnetwork in the same format as the original networks.