Package: mRMRe 2.1.2.2

Benjamin Haibe-Kains

mRMRe: Parallelized Minimum Redundancy, Maximum Relevance (mRMR)

Computes mutual information matrices from continuous, categorical and survival variables, as well as feature selection with minimum redundancy, maximum relevance (mRMR) and a new ensemble mRMR technique. Published in De Jay et al. (2013) <doi:10.1093/bioinformatics/btt383>.

Authors:Nicolas De Jay [aut], Simon Papillon-Cavanagh [aut], Catharina Olsen [aut], Gianluca Bontempi [aut], Bo Li [aut], Christopher Eeles [ctb], Benjamin Haibe-Kains [aut, cre]

mRMRe_2.1.2.2.tar.gz
mRMRe_2.1.2.2.tar.gz(r-4.7-arm64)mRMRe_2.1.2.2.tar.gz(r-4.7-x86_64)mRMRe_2.1.2.2.tar.gz(r-4.6-arm64)mRMRe_2.1.2.2.tar.gz(r-4.6-x86_64)
mRMRe_2.1.2.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
mRMRe/json (API)

# Install 'mRMRe' in R:
install.packages('mRMRe', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • cgps.annot - Part of the large pharmacogenomic dataset published by Garnett et al. within the Cancer Genome Project
  • cgps.ge - Part of the large pharmacogenomic dataset published by Garnett et al. within the Cancer Genome Project
  • cgps.ic50 - Part of the large pharmacogenomic dataset published by Garnett et al. within the Cancer Genome Project

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cppopenmp

5.66 score 1 stars 2 packages 139 scripts 5.4k downloads 27 mentions 33 exports 12 dependencies

Last updated from:2019541ad7. Checks:4 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE204
linux-devel-x86_64NOTE176
source / vignettesOK173
linux-release-arm64NOTE142
linux-release-x86_64NOTE158
wasm-releaseOK117

Exports:adjacencyMatrixadjacencyMatrixSumcausalitycorrelateexport_concordance_indexexport_filtersexport_filters_bootstrapexport_mimfeatureCountfeatureDatafeatureNamesget_thread_countget.thread.countmimmRMR.classicmRMR.datamRMR.ensemblemRMR.networkpriorspriors<-sampleCountsampleNamessampleStratasampleStrata<-sampleWeightssampleWeights<-scoresset_thread_countset.thread.countsolutionssubsetDatatargetvisualize

Dependencies:clicpp11glueigraphlatticelifecyclemagrittrMatrixpkgconfigrlangsurvivalvctrs

mRMRe: an R package for parallelized mRMR ensemble feature selection

Rendered frommRMRe.Rnwusingutils::Sweaveon Jun 02 2026.

Last update: 2021-05-27
Started: 2013-05-14

Readme and manuals

Help Manual

Help pageTopics
Accessor function for the 'adjacencyMatrix' information in a mRMRe.Network object.adjacencyMatrix adjacencyMatrix,mRMRe.Network-method adjacencyMatrixSum adjacencyMatrixSum,mRMRe.Network-method
Accessor function for the 'causality' information in a mRMRe.Filter and mRMRe.Network object.causality causality,mRMRe.Filter-method causality,mRMRe.Network-method
Part of the large pharmacogenomic dataset published by Garnett et al. within the Cancer Genome Project (CGP)cgps.annot cgps.ge cgps.ic50
Function to compute various correlation measures between two variablescorrelate
Export concordance indexexport_concordance_index
Export filtersexport_filters
Export filters bootstrapexport_filters_bootstrap
Export mimexport_mim
Accessor function for the 'featureCount' information in a mRMRe.Data, mRMRe.Filter and mRMRe.Network object.featureCount featureCount,mRMRe.Data-method featureCount,mRMRe.Filter-method featureCount,mRMRe.Network-method
Accessor function for the 'featureData' information in a mRMRe.Data objectfeatureData featureData,mRMRe.Data-method
Accessor function for the 'featureNames' information in a mRMRe.Data, mRMRe.Filter and mRMRe.Network objectfeatureNames featureNames,mRMRe.Data-method featureNames,mRMRe.Filter-method featureNames,mRMRe.Network-method
openMP Thread Countget_thread_count
openMP Thread Countget.thread.count
Accessor function for the 'mim' information in a mRMRe.Data, mRMRe.Filter and mRMRe.Network objectmim mim,mRMRe.Data-method mim,mRMRe.Filter-method mim,mRMRe.Network-method
Class '"mRMRe.Data"'mRMR.data mRMRe.Data-class
Class '"mRMRe.Filter"'mRMR.classic mRMR.ensemble mRMRe.Filter-class
Class '"mRMRe.Network"'mRMR.network mRMRe.Network-class
Accessor function for the 'priors' information in a mRMRe.Data objectpriors priors,mRMRe.Data-method priors<- priors<-,mRMRe.Data-method
Accessor function for the 'sampleCount' information in a mRMRe.Data, mRMRe.Filter and mRMRe.Network object.sampleCount sampleCount,mRMRe.Data-method sampleCount,mRMRe.Filter-method sampleCount,mRMRe.Network-method
Accessor function for the 'sampleNames' information in a mRMRe.Data, mRMRe.Filter and mRMRe.Network object.sampleNames sampleNames,mRMRe.Data-method sampleNames,mRMRe.Filter-method sampleNames,mRMRe.Network-method
Accessor function for the 'sampleStrata' information in a mRMRe.Data objectsampleStrata sampleStrata,mRMRe.Data-method sampleStrata<- sampleStrata<-,mRMRe.Data-method
Accessor function for the 'sampleWeights' information in a mRMRe.Data objectsampleWeights sampleWeights,mRMRe.Data-method sampleWeights<- sampleWeights<-,mRMRe.Data-method
mRMR Scores as per the MI gain for each featurescores scores,mRMRe.Data-method scores,mRMRe.Filter-method scores,mRMRe.Network-method
openMP Thread Countset_thread_count
openMP Thread Countset.thread.count
Basic result of the mRMR proceduresolutions solutions,mRMRe.Filter-method solutions,mRMRe.Network-method
Returns a mRMRe.Data object using a subset of the current mRMRe.Data object.subsetData subsetData,mRMRe.Data-method
mRMR Target(s)target target,mRMRe.Filter-method target,mRMRe.Network-method
mRMRe Network displayvisualize visualize,mRMRe.Network-method