PearsonSolver.Rd
Create a Solver class object using Pearson correlation coefficients as the solver
PearsonSolver( mtx.assay = matrix(), targetGene, candidateRegulators, quiet = TRUE )
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 |
quiet | A logical denoting whether or not the solver should print output |
A Solver class object with Pearson correlation coefficients as the solver
Other Solver class objects:
BayesSpikeSolver
,
EnsembleSolver
,
HumanDHSFilter-class
,
LassoPVSolver
,
LassoSolver
,
RandomForestSolver
,
RidgeSolver
,
Solver-class
,
SpearmanSolver
,
SqrtLassoSolver
,
XGBoostSolver
load(system.file(package="trena", "extdata/ampAD.154genes.mef2cTFs.278samples.RData")) target.gene <- "MEF2C" tfs <- setdiff(rownames(mtx.sub), target.gene) pearson.solver <- PearsonSolver(mtx.sub, target.gene, tfs)