FootprintFilter-class: Create a FootprintFilter object

In PriceLab/trena-until-01mar2018: Fit transcriptional regulatory networks using gene expression, priors, machine learning

Description

A FootprintFilter object allows for filtering based on gene footprinting databases. Using its associated getCandidates method and URIs for both a genome database and project database, a FootprintFilter object can be used to filter a list of possible transcription factors to those that match footprint motifs for a supplied target gene.

Usage

FootprintFilter(genomeDB, footprintDB, regions = data.frame(), quiet = TRUE)

Arguments

genomeDB	A connection to a database that contains genome information
footprintDB	A connection to a database that contains footprint information
regions	A data frame that specifies the regions of interest (default = data.frame())
quiet	A logical denoting whether or not the filter should print output

Value

An object of the FootprintFilter class

See Also

getCandidates-FootprintFilter

Other Filtering Objects: VarianceFilter-class

Examples

load(system.file(package="trena", "extdata/ampAD.154genes.mef2cTFs.278samples.RData"))
db.address <- system.file(package="trena", "extdata")
genome.db.uri <- paste("sqlite:/",db.address,"mef2c.neighborhood.hg38.gtfAnnotation.db", sep = "/")
project.db.uri <- paste("sqlite:/",db.address,"mef2c.neigborhood.hg38.footprints.db", sep = "/")
target.gene <- "MEF2C"
size.upstream <- 1000
size.downstream <- 1000

# Construct a Trena object and use it to retrive the regions
trena <- Trena("hg38")
regions <- getProximalPromoter(trena,target.gene, size.upstream, size.downstream)
 
footprint.filter <- FootprintFilter(genomeDB = genome.db.uri, footprintDB = project.db.uri,
regions = regions)

PriceLab/trena-until-01mar2018 documentation built on May 25, 2019, 1:22 p.m.