bootstrapViper: bootstrapsViper

Description Usage Arguments Value See Also Examples

View source: R/viper.r

Description

This function performs a viper analysis with bootstraps

Usage

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bootstrapViper(eset, regulon, nes = TRUE, bootstraps = 10,
  eset.filter = FALSE, adaptive.size = TRUE, minsize = 20,
  mvws = 1, cores = 1, verbose = TRUE)

Arguments

eset

ExpressionSet object or Numeric matrix containing the expression data, with samples in columns and genes in rows

regulon

Object of class regulon

nes

Logical, whether the enrichment score reported should be normalized

bootstraps

Integer indicating the number of bootstraps iterations to perform. Only the scale method is implemented with bootstraps.

eset.filter

Logical, whether the dataset should be limited only to the genes represented in the interactome

adaptive.size

Logical, whether the weighting scores should be taken into account for computing the regulon size

minsize

Integer indicating the minimum number of targets allowed per regulon

mvws

Number or vector indicating either the exponent score for the metaViper weights, or the inflection point and trend for the sigmoid function describing the weights in metaViper

cores

Integer indicating the number of cores to use (only 1 in Windows-based systems)

verbose

Logical, whether progression messages should be printed in the terminal

Value

A list containing a matrix of inferred activity for each regulator gene in the network across all samples and the corresponding standard deviation computed from the bootstrap iterations.

See Also

viper

Examples

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data(bcellViper, package="bcellViper")
d1 <- exprs(dset)
res <- viper(d1[, 1:50], regulon, bootstraps=10) # Run only on 50 samples to reduce computation time
dim(d1)
d1[1:5, 1:5]
regulon
dim(res$nes)
res$nes[1:5, 1:5]
res$sd[1:5, 1:5]

viper documentation built on Nov. 8, 2020, 7:37 p.m.