minepy - Maximal Information-based Nonparametric Exploration

https://travis-ci.org/minepy/minepy.png?branch=master Documentation Status

minepy provides an ANSI C library for the Maximal Information-based Nonparametric Exploration (MIC and MINE family). Key features:

  • APPROX-MIC (the original algorithm, DOI: 10.1126/science.1205438) and MIC_e (DOI: arXiv:1505.02213 and DOI: arXiv:1505.02214) estimators;
  • Total Information Coefficient (TIC, DOI: arXiv:1505.02213) and the Generalized Mean Information Coefficient (GMIC, DOI: arXiv:1308.5712);
  • a C++ interface;
  • an efficient Python API;
  • an efficient MATLAB/OCTAVE API;
  • a command-line application similar to the original MINE.jar;
  • the minerva R interface is available at CRAN.

minepy is an open-source, GPLv3-licensed software.

NEWS: MICtools, a comprehensive and effective pipeline for TICe and MICe analysis is now available. TICe is used to perform efficiently a high throughput screening of all the possible pairwise relationships assessing their significance, while MICe is used to rank the subset of significant associations on the bases of their strength. Paper: https://www.biorxiv.org/content/early/2017/11/07/215855, code and documentation: https://github.com/minepy/mictools. The minepy library is preinstalled in the Docker image: https://hub.docker.com/r/minepy/mictools/.

Citing minepy

Davide Albanese, Michele Filosi, Roberto Visintainer, Samantha Riccadonna, Giuseppe Jurman and Cesare Furlanello. minerva and minepy: a C engine for the MINE suite and its R, Python and MATLAB wrappers. Bioinformatics (2013) 29(3): 407-408 first published online December 14, 2012 doi:10.1093/bioinformatics/bts707.

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