getCandidates-FootprintFilter-method: Get candidate genes using the footprint filter

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

Description

Get candidate genes using the footprint filter

Usage

## S4 method for signature 'FootprintFilter'
getCandidates(obj)

Arguments

obj	An object of class FootprintFilter

Value

A list, where one element is the transcription factors found in the footprints and the other is a data frame containing all the meta data for the footprints

See Also

FootprintFilter

Other getCandidate Methods: getCandidates,GeneOntologyFilter-method, getCandidates,HumanDHSFilter-method, getCandidates,VarianceFilter-method, getCandidates

Examples

# Use footprint filter with the included SQLite database for MEF2C to filter candidates
# in the included Alzheimer's dataset, using the Trena object to get regions
target.gene <- "MEF2C"
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 = "/")
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)
footprints <- getCandidates(footprint.filter)

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