scoreDnf {bnem} | R Documentation

## score a boolean network

### Description

computes the score of a boolean network given the model and data

### Usage

    scoreDnf(
      bString,
      CNOlist,
      fc,
      expression = NULL,
      model,
      method = "cosine",
      sizeFac = 10^-10,
      NAFac = 1,
      parameters = list(cutOffs = c(0, 1, 0), scoring = c(0.25, 0.5, 2)),
      NEMlist = NULL,
      relFit = FALSE,
      verbose = FALSE
    )

### Arguments

`bString` | binary string denoting the boolean network
`CNOlist` | CNOlist object (see package CellNOptR), if available.
`fc` | m x l matrix of foldchanges of gene expression values or equivalent input (normalized pvalues, logodds, ...) for m E-genes and l contrasts. If left NULL, the gene expression data is used to calculate naive foldchanges.
`expression` | Optional normalized m x l matrix of gene expression data for m E-genes and l experiments.
`model` | Model object including the search space, if available. See CellNOptR::preprocessing.
`method` | Scoring method can be "cosine", a correlation, or a distance measure. See ?cor and ?dist for details.
`sizeFac` | Size factor penelizing the hyper-graph size.
`NAFac` | factor penelizing NAs in the data.
`parameters` | parameters for discrete case (not recommended); has to be a list with entries cutOffs and scoring: cutOffs = c(a,b,c) with a (cutoff for real zeros), b (cutoff for real effects), c = -1 for normal scoring, c between 0 and 1 for keeping only relevant between -1 and 0 for keeping only a specific quantile of E-genes, and c > 1 for keeping the top c E-genes; scoring = c(a,b,c) with a (weight for real effects), c (weight for real zeros), b (multiplicator for effects/zeros between a and c);
`NEMlist` | NEMlist object (optional)
`relFit` | if TRUE a relative fit for each E-gene is computed (not recommended)
`verbose` | TRUE for verbose output

### Value

numeric value (score)

### Author(s)

Martin Pirkl

### Examples

    sim <- simBoolGtn()
    scoreDnf(sim$bString, sim$CNOlist, sim$fc, model=sim$model)

[Package bnem version 1.2.0 Index]