viper (version 1.6.0)

msviper: msVIPER

Description

This function performs MAster Regulator INference Analysis

Usage

msviper(ges, regulon, nullmodel = NULL, pleiotropy = FALSE, minsize = 25, adaptive.size = FALSE, ges.filter = TRUE, synergy = 0, level = 10, pleiotropyArgs = list(regulators = 0.05, shadow = 0.05, targets = 10, penalty = 20, method = "adaptive"), cores = 1, verbose = TRUE)

Arguments

ges

Vector containing the gene expression signature to analyze, or matrix with columns containing bootstraped signatures

regulon

Object of class regulon

nullmodel

Matrix of genes by permutations containing the NULL model signatures. A parametric approach equivalent to shuffle genes will be used if nullmodel is ommitted.

pleiotropy

Logical, whether correction for pleiotropic regulation should be performed

minsize

Number indicating the minimum allowed size for the regulons

adaptive.size

Logical, whether the weight (likelihood) should be used for computing the regulon size

ges.filter

Logical, whether the gene expression signature should be limited to the genes represented in the interactome

synergy

Number indicating the synergy computation mode: (0) for no synergy computation; (0-1) for establishing the p-value cutoff for individual TFs to be included in the synergy analysis; (>1) number of top TFs to be included in the synergy analysis

level

Integer, maximum level of combinatorial regulation

pleiotropyArgs

list of 5 numbers for the pleotropy correction indicating: regulators p-value threshold, pleiotropic interaction p-value threshold, minimum number of targets in the overlap between pleiotropic regulators, penalty for the pleiotropic interactions and the pleiotropy analysis method, either absolute or adaptive

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 msviper object containing the following components:

signature

The gene expression signature

regulon

The final regulon object used

es

Enrichment analysis results including regulon size, normalized enrichment score and p-value

param

msviper parameters, including minsize, adaptive.size

See Also

viper

Examples

data(bcellViper, package="bcellViper")
sig <- rowTtest(dset, "description", c("CB", "CC"), "N")$statistic
dnull <- ttestNull(dset, "description", c("CB", "CC"), "N", per=100) # Only 100 permutations to reduce computation time, but it is recommended to perform at least 1000 permutations
mra <- msviper(sig, regulon, dnull)
plot(mra, cex=.7)