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

• Published in: Bioinformatics Vol. 29; no. 3; pp. 407 - 408
• Main Authors: Albanese, Davide, Filosi, Michele, Visintainer, Roberto, Riccadonna, Samantha, Jurman, Giuseppe, Furlanello, Cesare
• Format: Journal Article
• Language: English
• Published: England 01.02.2013
• Subjects: Algorithms; Computational Biology; Data Mining; Gene Expression Profiling; Metagenome; Software
• ISSN: 1367-4803; 1367-4811; 1367-4811; 1460-2059
• DOI: 10.1093/bioinformatics/bts707

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 ( = 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). Contact:  furlan@fbk.eu Supplementary information:  Supplementary data are available at Bioinformatics online.