run,EnsembleSolver-method {trena} | R Documentation

## Run the Ensemble Solver

### Description

Given a TReNA object with Ensemble as the solver and a list of solvers (default = "default.solvers"), estimate coefficients for each transcription factor as a predictor of the target gene's expression level. The final scores for the ensemble method combine all specified solvers to create a composite score for each transcription factor. This method should be called using the `solve` method on an appropriate TReNA object.

### Usage

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

### Arguments

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

### Details

- concordancea composite score

- pcaMaxa composite of the principal components of the individual solver scores

### Value

A data frame containing the scores for all solvers and two composite scores relating the target gene to each transcription factor. The two new scores are:

### See Also

`EnsembleSolver`

Other solver methods: `run,BayesSpikeSolver-method`, `run,BicorSolver-method`, `run,LassoPVSolver-method`, `run,LassoSolver-method`, `run,PearsonSolver-method`, `run,RandomForestSolver-method`, `run,RidgeSolver-method`, `run,SpearmanSolver-method`, `run,XGBoostSolver-method`

### Examples

    ## Not run:
    # Load included Alzheimer's data, create an Ensemble object with default solvers, and solve
    load(system.file(package="trena", "extdata/ampAD.154genes.mef2cTFs.278samples.RData"))
    target.gene <- "MEF2C"
    tfs <- setdiff(rownames(mtx.sub), target.gene)[1:30]
    ensemble.solver <- EnsembleSolver(mtx.sub, target.gene, tfs)
    tbl <- run(ensemble.solver)

    # Solve the same problem, but supply extra arguments that change alpha for LASSO to 0.8 and also
    # Change the gene cutoff from 10% to 20%
    ensemble.solver <- EnsembleSolver(mtx.sub, target.gene, tfs, geneCutoff = 0.2, alpha.lasso = 0.8)
    tbl <- run(ensemble.solver)

    # Solve the original problem with default cutoff and solver parameters, but use only 4 solvers
    ensemble.solver <- EnsembleSolver(mtx.sub, target.gene, tfs,
    solverNames = c("lasso", "pearson", "ridge"))
    tbl <- run(ensemble.solver)

    ## End(Not run)

[Package trena version 1.16.0 Index]