validateGraph: validate graph

In MartinFXP/bnem: Training of logical models from indirect measurements of perturbation experiments

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)

MartinFXP/bnem documentation built on Nov. 5, 2024, 11:57 a.m.