Package: mRMRe 2.1.2

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.tar.gz
mRMRe_2.1.2.zip(r-4.7-x86_64)mRMRe_2.1.2.zip(r-4.7-arm64)mRMRe_2.1.2.zip(r-4.6-x86_64)mRMRe_2.1.2.zip(r-4.6-arm64)mRMRe_2.1.2.zip(r-4.5-x86_64)
mRMRe_2.1.2.tgz(r-4.6-x86_64)mRMRe_2.1.2.tgz(r-4.6-arm64)mRMRe_2.1.2.tgz(r-4.5-x86_64)mRMRe_2.1.2.tgz(r-4.5-arm64)
mRMRe_2.1.2.tar.gz(r-4.7-arm64)mRMRe_2.1.2.tar.gz(r-4.7-x86_64)mRMRe_2.1.2.tar.gz(r-4.6-arm64)mRMRe_2.1.2.tar.gz(r-4.6-x86_64)
mRMRe_2.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
mRMRe/json (API)

# Install 'mRMRe' in R:

install.packages('mRMRe', repos = c('https://bhklab.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bhklab/mrmre/issues

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:

cpp openmp

9.22 score 21 stars 2 packages 146 scripts 2.6k downloads 27 mentions 33 exports 12 dependencies

Last updated from:ea904c0f9f. Checks:4 NOTE, 2 OK, 9 WARNING. Indexed: yes.

Target	Result	Time
linux-devel-arm64	NOTE	120
linux-devel-x86_64	NOTE	161
source / vignettes	OK	215
linux-release-arm64	WARNING	124
linux-release-x86_64	WARNING	143
macos-release-arm64	WARNING	257
macos-release-x86_64	WARNING	242
macos-oldrel-arm64	WARNING	255
macos-oldrel-x86_64	WARNING	729
windows-devel-arm64	NOTE	331
windows-devel-x86_64	NOTE	143
windows-release-arm64	WARNING	329
windows-release-x86_64	WARNING	120
windows-oldrel-x86_64	WARNING	99
wasm-release	OK	128

Exports:adjacencyMatrix adjacencyMatrixSum causality correlate export_concordance_index export_filters export_filters_bootstrap export_mim featureCount featureData featureNames get_thread_count get.thread.count mim mRMR.classic mRMR.data mRMR.ensemble mRMR.network priors priors<-sampleCount sampleNames sampleStrata sampleStrata<-sampleWeights sampleWeights<-scores set_thread_count set.thread.count solutions subsetData target visualize

Dependencies:cli cpp11 glue igraph lattice lifecycle magrittr Matrix pkgconfig rlang survival vctrs

mRMRe: an R package for parallelized mRMR ensemble feature selection

Rendered frommRMRe.Rnwusingutils::Sweave

Last update: 2020-01-22
Started: 2014-09-16

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
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 variables	correlate
Export concordance index	export_concordance_index
Export filters	export_filters
Export filters bootstrap	export_filters_bootstrap
Export mim	export_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 object	featureData featureData,mRMRe.Data-method
Accessor function for the 'featureNames' information in a mRMRe.Data, mRMRe.Filter and mRMRe.Network object	featureNames featureNames,mRMRe.Data-method featureNames,mRMRe.Filter-method featureNames,mRMRe.Network-method
openMP Thread Count	get_thread_count
openMP Thread Count	get.thread.count
Accessor function for the 'mim' information in a mRMRe.Data, mRMRe.Filter and mRMRe.Network object	mim 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 object	priors 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 object	sampleStrata sampleStrata,mRMRe.Data-method sampleStrata<- sampleStrata<-,mRMRe.Data-method
Accessor function for the 'sampleWeights' information in a mRMRe.Data object	sampleWeights sampleWeights,mRMRe.Data-method sampleWeights<- sampleWeights<-,mRMRe.Data-method
mRMR Scores as per the MI gain for each feature	scores scores,mRMRe.Data-method scores,mRMRe.Filter-method scores,mRMRe.Network-method
openMP Thread Count	set_thread_count
openMP Thread Count	set.thread.count
Basic result of the mRMR procedure	solutions 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 display	visualize visualize,mRMRe.Network-method