HumanDHSFilter-class: Create a HumanDHSFilter object

In PriceLab/TReNA: Fit transcriptional regulatory networks using gene expression, priors, machine learning

Create a HumanDHSFilter object

Description

A HumanDHSFilter object allows for filtering based on DNAse hypersensitivity (DHS) data. Its associated getCandidates method uses a genome from a BSgenome database (either hg19 or hg38), DNA region specifications, and (variants/pfms,encodetablename, match to filter a list of possible regulators factors to those that match the supplied criteria.

Usage

HumanDHSFilter(
  genomeName,
  encodeTableName = "wgEncodeRegDnaseClustered",
  pwmMatchPercentageThreshold,
  geneInfoDatabase.uri,
  regions,
  variants = NA_character_,
  pfms,
  quiet = TRUE
)

Arguments

genomeName	A character string indicating the reference genome; currently, the only accepted strings are "hg38" and "hg19", both of which are human genomes.
encodeTableName	(default = "wgEncodeRegDnaseClustered")
pwmMatchPercentageThreshold	A numeric from 0-100 to serve as a threshold for a match
geneInfoDatabase.uri	An address for a gene database
regions	A data frame containing the regions of interest
variants	A character vector containing a list of variants
pfms	A list of position frequency matrices, often converted from a MotifList object created by a MotifDb query
quiet	A logical denoting whether or not the solver should print output

Value

A CandidateFilter class object that filters using Human DHS data

See Also

getCandidates-HumanDHSFilter,

Other Solver class objects: BicorSolver, EnsembleSolver, LassoPVSolver, LassoSolver, PearsonSolver, RandomForestSolver, RidgeSolver, Solver-class, SpearmanSolver, XGBoostSolver

Examples

if(interactive()) { # takes too long in the bioc windows build
  load(system.file(package="trena", "extdata/ampAD.154genes.mef2cTFs.278samples.RData"))
  targetGene <- "VRK2"
  promoter.length <- 1000
  genomeName <- "hg38"
  db.address <- system.file(package="trena", "extdata")
  genome.db.uri    <- paste("sqlite:/", db.address, "vrk2.neighborhood.hg38.gtfAnnotation.db",  sep = "/")

    # Grab regions for VRK2 using shoulder size of 1000
  trena <- Trena(genomeName)
  tbl.regions <- getProximalPromoter(trena, "VRK2", 1000, 1000)

  hd.filter <- HumanDHSFilter(genomeName, pwmMatchPercentageThreshold = 85,
  geneInfoDatabase.uri = genome.db.uri, regions = tbl.regions,
   pfms = as.list(query(query(MotifDb, "sapiens"),"jaspar2016")))
   } # if interactive

PriceLab/TReNA documentation built on March 21, 2023, 1:57 p.m.