solve.Lasso: Run the LASSO Solver

Description Usage Arguments Value See Also Examples

Description

Given a LassoSolver object, use the glmnet function to estimate coefficients for each transcription factor as a predictor of the target gene's expression level.

Usage

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## S4 method for signature 'LassoSolver'
run(obj)

Arguments

obj

An object of class LassoSolver

Value

A data frame containing the coefficients relating the target gene to each transcription factor, plus other fit parameters.

See Also

glmnet,, LassoSolver

Other solver methods: run,BayesSpikeSolver-method, run,EnsembleSolver-method, run,LassoPVSolver-method, run,PearsonSolver-method, run,RandomForestSolver-method, run,RidgeSolver-method, run,SpearmanSolver-method, run,XGBoostSolver-method

Examples

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# Load included Alzheimer's data, create a TReNA object with LASSO as solver, and solve
load(system.file(package="trena", "extdata/ampAD.154genes.mef2cTFs.278samples.RData"))
target.gene <- "MEF2C"
tfs <- setdiff(rownames(mtx.sub), target.gene)
lasso.solver <- LassoSolver(mtx.sub, target.gene, tfs)
tbl <- run(lasso.solver)

trena documentation built on Nov. 15, 2020, 2:07 a.m.