run,LassoPVSolver-method {trena} | R Documentation

## Run the LASSO P-Value Solver

### Description

Given 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.

### Usage

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

### Arguments

`obj` | An object of class LassoPVSolver

### Value

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.

### See Also

`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,XGBoostSolver-method`

### Examples

    # 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)

[Package trena version 1.14.0 Index]