run,SqrtLassoSolver-method {trena} | R Documentation

## Run the Square Root LASSO Solver

### Description

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

### Usage

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

### Arguments

`obj` | An object of class Solver with "sqrtlasso" as the solver string

### Value

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

### See Also

`slim`, `SqrtLassoSolver`

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`

### Examples

    # 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)

[Package trena version 1.2.0 Index]