CandidateFilter-class: CandidateFilter

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

Description

A CandidateFilter is an S4 class to represent a gene candidate filter. These filters can employ a variety of methods to reduce the number of transcription factors used as predictors for solving a TReNA object.

Usage

CandidateFilter(mtx.assay = matrix(), quiet = TRUE)

## S4 method for signature 'CandidateFilter'
getFilterAssayData(obj)

Arguments

mtx.assay	An assay matrix of gene expression data
quiet	A logical denoting whether or not the CandidateFilter object should print output
obj	An object of a CandidateFilter class

Value

An object of the Candidate filter class

Methods (by generic)

• getFilterAssayData: Retrieve the assay matrix of gene expression data

Slots

mtx.assay

An assay matrix of gene expression data

quiet

A logical denoting whether or not the CandidateFilter object should print output

See Also

getCandidates, getFilterAssayData

Examples

# Create an empty candidate filter
candidate.filter <- CandidateFilter(mtx.assay = matrix(), quiet=TRUE)

# Create a CandidateFilter object using the included Alzheimer's data and retrieve the matrix
load(system.file(package="TReNA", "extdata/ampAD.154genes.mef2cTFs.278samples.RData"))
my.filter <- CandidateFilter(mtx.sub)
mtx <- getFilterAssayData(my.filter)

TReNA documentation built on Nov. 17, 2017, 12:35 p.m.