validateGraph {bnem} | R Documentation

## validate graph

### Description

plotting the observed differential effects of an effect reporter and the expected differential effects of the regulating signalling gene

### Usage

    validateGraph(
      CNOlist,
      fc = NULL,
      expression = NULL,
      model,
      bString,
      Egenes = 25,
      Sgene = 1,
      parameters = list(cutOffs = c(0, 1, 0), scoring = c(0.1, 0.2, 0.9)),
      plot = TRUE,
      disc = 0,
      affyIds = TRUE,
      relFit = FALSE,
      xrot = 25,
      Rowv = FALSE,
      Colv = FALSE,
      dendrogram = "none",
      soft = TRUE,
      colSideColors = NULL,
      affychip = "hgu133plus2",
      method = "s",
      ranks = FALSE,
      breaks = NULL,
      col = "RdYlGn",
      sizeFac = 10^-10,
      order = "rank",
      verbose = TRUE,
      ...
    )

### Arguments

`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.
`bString` | Binary string denoting the hyper-graph.
`Egenes` | Maximal number of visualized E-genes.
`Sgene` | Integer denoting the S-gene. See colnames(getSignals(CNOlist)[[1]]) to match integer with S-gene name.
`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);
`plot` | Plot the heatmap. If FALSE, only corresponding information is printed.
`disc` | Discretize the data.
`affyIds` | Experimental. Turn Affymetrix Ids into HGNC gene symbols.
`relFit` | if TRUE a relative fit for each E-gene is computed (not recommended)
`xrot` | See function epiNEM::HeatmapOP
`Rowv` | See function epiNEM::HeatmapOP
`Colv` | See function epiNEM::HeatmapOP
`dendrogram` | See function epiNEM::HeatmapOP
`soft` | if TRUE, assigns weights to the expected pattern
`colSideColors` | See function epiNEM::HeatmapOP
`affychip` | Define Affymetrix chip used to generate the data (optional and experimental).
`method` | Scoring method can be "cosine", a correlation, or a distance measure. See ?cor and ?dist for details.
`ranks` | if TRUE, turns data into ranks
`breaks` | See function epiNEM::HeatmapOP
`col` | See function epiNEM::HeatmapOP
`sizeFac` | Size factor penelizing the hyper-graph size.
`order` | Order by "rank", "name" or "none"
`verbose` | TRUE for verbose output
`...` | additional arguments for epiNEM::HeatmapOP

### Value

lattice object with matrix information

### Author(s)

Martin Pirkl

### Examples

    sifMatrix <- rbind(c("A", 1, "B"), c("A", 1, "C"), c("B", 1, "D"),
    c("C", 1, "D"))
    temp.file <- tempfile(pattern="interaction",fileext=".sif")
    write.table(sifMatrix, file = temp.file, sep = "\t",
    row.names = FALSE, col.names = FALSE,
    quote = FALSE)
    PKN <- CellNOptR::readSIF(temp.file)
    CNOlist <- dummyCNOlist("A", c("B","C","D"), maxStim = 1, maxInhibit = 2,
    signal = c("A", "B","C","D"))
    model <- CellNOptR::preprocessing(CNOlist, PKN, maxInputsPerGate = 100)
    expression <- matrix(rnorm(nrow(slot(CNOlist, "cues"))*10), 10,
    nrow(slot(CNOlist, "cues")))
    fc <- computeFc(CNOlist, expression)
    initBstring <- rep(0, length(model$reacID))
    res <- bnem(search = "greedy", CNOlist = CNOlist, fc = fc,
    model = model, parallel = NULL, initBstring = initBstring, draw = FALSE,
    verbose = FALSE, maxSteps = Inf)
    rownames(fc) <- seq_len(nrow(fc))
    val <- validateGraph(CNOlist = CNOlist, fc = fc, model = model,
    bString = res$bString, Egenes = 10, Sgene = 4)

[Package bnem version 1.2.0 Index]