English

Minerva and minepy: a C engine for the MINE suite and its R, Python and MATLAB wrappers

Machine Learning 2012-12-17 v2 Quantitative Methods

Abstract

We introduce a novel implementation in ANSI C of the MINE family of algorithms for computing maximal information-based measures of dependence between two variables in large datasets, with the aim of a low memory footprint and ease of integration within bioinformatics pipelines. We provide the libraries minerva (with the R interface) and minepy for Python, MATLAB, Octave and C++. The C solution reduces the large memory requirement of the original Java implementation, has good upscaling properties, and offers a native parallelization for the R interface. Low memory requirements are demonstrated on the MINE benchmarks as well as on large (n=1340) microarray and Illumina GAII RNA-seq transcriptomics datasets. Availability and Implementation: Source code and binaries are freely available for download under GPL3 licence at http://minepy.sourceforge.net for minepy and through the CRAN repository http://cran.r-project.org for the R package minerva. All software is multiplatform (MS Windows, Linux and OSX).

Cite

@article{arxiv.1208.4271,
  title  = {Minerva and minepy: a C engine for the MINE suite and its R, Python and MATLAB wrappers},
  author = {Davide Albanese and Michele Filosi and Roberto Visintainer and Samantha Riccadonna and Giuseppe Jurman and Cesare Furlanello},
  journal= {arXiv preprint arXiv:1208.4271},
  year   = {2012}
}

Comments

Bioinformatics 2012, in press

R2 v1 2026-06-21T21:53:30.310Z