plot.bnembs: Plot Bootstrap result

Description Usage Arguments Value Author(s) Examples

View source: R/bnem_main.r

Description

Shows the result of a Boostrap with either edge frequencies or confidence intervals

Usage

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## S3 method for class 'bnembs'
plot(
  x,
  scale = 3,
  shift = 0.1,
  cut = 0.5,
  dec = 2,
  ci = 0,
  cip = 0.95,
  method = "exact",
  ...
)

Arguments

x

bnembs object

scale

numeric value for scaling the edgewidth

shift

numeric value for shifting the edgewidth

cut

shows only edges with a fraction larger than cut

dec

integer for function round

ci

if TRUE shows confidence intervals

cip

range for the confidence interval, e.g. 0.95

method

method to use for conidence itneral computation (see function binom.confint from package binom)

...

additional parameters for the function mnem::plotDnf from package mnem

Value

plot of the network from the bootstrap

Author(s)

Martin Pirkl

Examples

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sifMatrix <- rbind(c("A", 1, "B"), c("A", 1, "C"), c("B", 1, "D"),
c("C", 1, "D"))
write.table(sifMatrix, file = "temp.sif", sep = "\t",
row.names = FALSE, col.names = FALSE,
quote = FALSE)
PKN <- CellNOptR::readSIF("temp.sif")
unlink('temp.sif')
CNOlist <- dummyCNOlist("A", c("B","C","D"), maxStim = 1,
maxInhibit = 2, signals = c("A", "B","C","D"))
model <- CellNOptR::preprocessing(CNOlist, PKN, maxInputsPerGate = 100)
exprs <- matrix(rnorm(nrow(slot(CNOlist, "cues"))*10), 10,
nrow(slot(CNOlist, "cues")))
fc <- computeFc(CNOlist, exprs)
initBstring <- rep(0, length(model$reacID))
res <- bnemBs(search = "greedy", model = model, CNOlist = CNOlist,
fc = fc, pkn = PKN, stimuli = "A", inhibitors = c("B","C","D"),
parallel = NULL, initBstring = initBstring, draw = FALSE, verbose = FALSE,
maxSteps = Inf)

MartinFXP/B-NEM documentation built on Aug. 30, 2020, 8:22 a.m.