Given a PearsonSolver object, use the cor function to estimate coefficients for each transcription factor as a predictor of the target gene's expression level.

# S4 method for PearsonSolver
run(obj)

Arguments

obj

An object of class PearsonSolver

Value

The set of Pearson Correlation Coefficients between each transcription factor and the target gene.

See also

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) pearson.solver <- PearsonSolver(mtx.sub, target.gene, tfs) tbl <- run(pearson.solver)