module_NMF: module_NMF

In miRSM: Inferring miRNA sponge modules in heterogeneous data

Description

Identification of gene modules from matched ceRNA and mRNA expression data using NMF package

Usage

module_NMF(
  ceRExp,
  mRExp,
  NMF.algorithm = "brunet",
  num.modules = 10,
  num.ModuleceRs = 2,
  num.ModulemRs = 2
)

Arguments

ceRExp	A SummarizedExperiment object. ceRNA expression data: rows are samples and columns are ceRNAs.
mRExp	A SummarizedExperiment object. mRNA expression data: rows are samples and columns are mRNAs.
NMF.algorithm	Specification of the NMF algorithm, including 'brunet' (default), 'Frobenius', 'KL', 'lee', 'nsNMF', 'offset', 'siNMF', 'snmf/l', 'snmf/r'.
num.modules	The number of modules to be identified.
num.ModuleceRs	The minimum number of ceRNAs in each module.
num.ModulemRs	The minimum number of mRNAs in each module.

Value

GeneSetCollection object: a list of module genes.

Author(s)

Junpeng Zhang (https://www.researchgate.net/profile/Junpeng_Zhang3)

References

Gaujoux R, Seoighe C. A flexible R package for nonnegative matrix factorization. BMC Bioinformatics. 2010, 11:367.

Examples

data(BRCASampleData)
# Reimport NMF package to avoid conflicts with DelayedArray package
library(NMF)
modulegenes_NMF <- module_NMF(ceRExp[, seq_len(10)],
    mRExp[, seq_len(10)])

miRSM documentation built on April 16, 2021, 6 p.m.