run,SqrtLassoSolver-method {trena} | R Documentation |
Given SqrtLassoSolver object, use the slim
function to
estimate coefficients for each transcription factor as a predictor of the
target gene's expression level.
## S4 method for signature 'SqrtLassoSolver' run(obj)
obj |
An object of class Solver with "sqrtlasso" as the solver string |
A data frame containing the coefficients relating the target gene to each transcription factor, plus other fit parameters.
Other solver methods: run,BayesSpikeSolver-method
,
run,EnsembleSolver-method
,
run,LassoPVSolver-method
,
run,LassoSolver-method
,
run,PearsonSolver-method
,
run,RandomForestSolver-method
,
run,RidgeSolver-method
,
run,SpearmanSolver-method
# Load included Alzheimer's data, create a TReNA object with Square Root LASSO as solver, # and run using a few predictors ## Not run: load(system.file(package="trena", "extdata/ampAD.154genes.mef2cTFs.278samples.RData")) target.gene <- "MEF2C" # Designate just 5 predictors and run the solver tfs <- setdiff(rownames(mtx.sub), target.gene)[1:5] sqrt.solver <- SqrtLassoSolver(mtx.sub, target.gene, tfs) tbl <- run(sqrt.solver) ## End(Not run)