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.

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

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