A practical tool for maximal information coefficient analysis.

ABSTRACT:

Background

The ability of finding complex associations in large omics datasets, assessing their significance, and prioritizing them according to their strength can be of great help in the data exploration phase. Mutual information-based measures of association are particularly promising, in particular after the recent introduction of the TICe and MICe estimators, which combine computational efficiency with superior bias/variance properties. An open-source software implementation of these two measures providing a complete procedure to test their significance would be extremely useful.

Findings

Here, we present MICtools, a comprehensive and effective pipeline that combines TICe and MICe into a multistep procedure that allows the identification of relationships of various degre

SUBMITTER: Albanese D 

PROVIDER: S-EPMC5893960 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature