RandomForestSolver {trena} | R Documentation

## Create a Solver class object using the Random Forest solver

### Description

Create a Solver class object using the Random Forest solver

### Usage

    RandomForestSolver(
      mtx.assay = matrix(),
      targetGene,
      candidateRegulators,
      regulatorWeights = rep(1, length(candidateRegulators)),
      quiet = TRUE
    )

### Arguments

`mtx.assay` | An assay matrix of gene expression data
`targetGene` | A designated target gene that should be part of the mtx.assay data
`candidateRegulators` | The designated set of transcription factors that could be associated with the target gene
`regulatorWeights` | A set of weights on the transcription factors (default = rep(1, length(candidateRegulators)))
`quiet` | A logical denoting whether or not the solver should print output

### Value

A Solver class object with Random Forest as the solver

### See Also

`solve.RandomForest`, `getAssayData`

Other Solver class objects: `BayesSpikeSolver`, `BicorSolver`, `EnsembleSolver`, `HumanDHSFilter-class`, `LassoPVSolver`, `LassoSolver`, `PearsonSolver`, `RidgeSolver`, `Solver-class`, `SpearmanSolver`, `XGBoostSolver`

### Examples

    load(system.file(package="trena", "extdata/ampAD.154genes.mef2cTFs.278samples.RData"))
    targetGene <- "MEF2C"
    candidateRegulators <- setdiff(rownames(mtx.sub), targetGene)
    rf.solver <- RandomForestSolver(mtx.sub, targetGene, candidateRegulators)

[Package trena version 1.16.0 Index]