miRSM {miRSM}R Documentation

miRSM

Description

Identify miRNA sponge modules using canonical correlation (CC), sensitivity canonical correlation (SCC), and integrate canonical correlation and sensitivity canonical correlation (CCplusSCC) methods.

Usage

miRSM(miRExp, ceRExp, mRExp, miRTarget, CandidateModulegenes,
  typex = "standard", typez = "standard", nperms = 100,
  method = c("CC", "SCC", "CCplusSCC"), num_shared_miRNAs = 3,
  pvalue.cutoff = 0.05, CC.cutoff = 0.8, SCC.cutoff = 0.3)

Arguments

miRExp

A SummarizedExperiment object. miRNA expression data: rows are samples and columns are miRNAs.

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.

miRTarget

A SummarizedExperiment object. Putative miRNA-target binding information.

CandidateModulegenes

List object: a list of candidate miRNA sponge modules.

typex

The columns of x unordered (type='standard') or ordered (type='ordered').

typez

The columns of z unordered (type='standard') or ordered (type='ordered').

nperms

The number of permutations.

method

The method selected to identify miRNA sponge modules, including 'CC', 'SCC' and 'CCplusSCC'.

num_shared_miRNAs

The number of common miRNAs shared by a group of ceRNAs and mRNAs.

pvalue.cutoff

The p-value cutoff of significant sharing of common miRNAs by a group of ceRNAs and mRNAs.

CC.cutoff

The cutoff of canonical correlation for 'CC' method.

SCC.cutoff

The cutoff of sensitivity canonical correlation for 'SCC' method.

Value

List object: Canonical correlation or sensitivity canonical correlation, and genes of miRNA sponge modules.

Author(s)

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

References

Witten DM, Tibshirani R, Hastie T. A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis. Biostatistics. 2009, 10(3):515-34.

Examples

data(BRCASampleData)
modulegenes_igraph <- module_igraph(ceRExp[, seq_len(10)], 
    mRExp[, seq_len(10)])
# Identify miRNA sponge modules using canonical correlation (CC)
miRSM_igraph_CC <- miRSM(miRExp, ceRExp, mRExp, miRTarget,
                        modulegenes_igraph, nperms = 5,
                        method = 'CC')


[Package miRSM version 1.2.0 Index]