solve.LassoPV.RdGiven a TReNA object with LASSO P-Value as the solver, use the lassopv
function to estimate coefficients for each transcription factor as a predictor of the target
gene's expression level.
# S4 method for LassoPVSolver run(obj)
| obj | An object of class LassoPVSolver |
|---|
A data frame containing the p-values for each transcription factor pertaining to the target gene plus the Pearson correlations between each transcription factor and the target gene.
lassopv, , LassoPVSolver
Other solver methods:
run,BayesSpikeSolver-method,
run,EnsembleSolver-method,
run,LassoSolver-method,
run,PearsonSolver-method,
run,RandomForestSolver-method,
run,RidgeSolver-method,
run,SpearmanSolver-method,
run,SqrtLassoSolver-method,
run,XGBoostSolver-method
# Load included Alzheimer's data, create a TReNA object with Bayes Spike 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) lassopv.solver <- LassoPVSolver(mtx.sub, target.gene, tfs) tbl <- run(lassopv.solver)