bootstrap.build: Perform network inference with bootstrap approach.

Description Usage Arguments Value Examples

Description

Perform network inference with bootstrap approach.

Usage

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bootstrap.build(expr, nboot = 10, nkeep1 = round(0.1 * nrow(expr)^2/2),
  nkeep2 = round(0.5 * nboot), parallel = FALSE, ncores = 10,
  seeds = NULL, ...)

Arguments

expr

a n by d data matrix

nboot

number of bootstrap samples

nkeep1

number of edges to keep from each infered network

nkeep2

minimum number of times an edge has to be predicted to be kept in the final network

parallel

should the function be run in parallel (unix-like systems only)

ncores

number of cores for parallel executions

seeds

vector of nboot seeds to control randomness in network inference based on bootstraps

...

options passed to the function set.options

Value

object with the following entries

Examples

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data(cancer)
# no constraint
res <- bootstrap.build(expr, nboot=3, nkeep1=10, nkeep2=1)
# constraints
res <- bootstrap.build(expr, nboot=3, nkeep1=10, nkeep2=1,
                       first.list=matrix(c("AMFR","BB_S4","BECNI","BTG3"),
                                         ncol=2, byrow=TRUE),
                       second.list=matrix(c("AMFR","E2F3"), ncol=2),
                       mu=1)
print(res)

tuxette/internet3D documentation built on May 8, 2019, 11:59 p.m.