solve.Ensemble: Run the Ensemble Solver

In PriceLab/TReNA: Fit transcriptional regulatory networks using gene expression, priors, machine learning

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,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)

PriceLab/TReNA documentation built on March 21, 2023, 1:57 p.m.