Package: mRMRe 2.1.2.2
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:
mRMRe_2.1.2.2.tar.gz
mRMRe_2.1.2.2.tar.gz(r-4.5-noble)mRMRe_2.1.2.2.tar.gz(r-4.4-noble)
mRMRe_2.1.2.2.tgz(r-4.4-emscripten)mRMRe_2.1.2.2.tgz(r-4.3-emscripten)
mRMRe.pdf |mRMRe.html✨
mRMRe/json (API)
# Install 'mRMRe' in R: |
install.packages('mRMRe', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- 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
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 30 days agofrom:2019541ad7. Checks:OK: 1 NOTE: 1. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 06 2024 |
R-4.5-linux-x86_64 | NOTE | Nov 06 2024 |
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