scholarly journals A practical tool for maximal information coefficient analysis

GigaScience ◽  
2018 ◽  
Vol 7 (4) ◽  
Author(s):  
Davide Albanese ◽  
Samantha Riccadonna ◽  
Claudio Donati ◽  
Pietro Franceschi
Keyword(s):  
Practical Tool ◽  
Information Coefficient ◽  
Maximal Information Coefficient

scholarly journals A practical tool for Maximal Information Coefficient analysis

2017 ◽  
Author(s):  
Davide Albanese ◽  
Samantha Riccadonna ◽  
Claudio Donati ◽  
Pietro Franceschi
Keyword(s):  
Statistical Significance ◽  
Metagenomic Dataset ◽  
Measures Of Association ◽  
Step Procedure ◽  
Practical Tool ◽  
Two Measures ◽  
Information Coefficient ◽  
Bias Variance ◽  
Synthetic Datasets ◽  
Maximal Information Coefficient

AbstractBackgroundThe 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 TICeand MICeestimators, which combine computational efficiency with good bias/variance properties. Despite that, a complete software implementation of these two measures and of a statistical procedure to test the significance of each association is still missing.FindingsIn this paper we present MICtools, a comprehensive and effective pipeline which combines TICeand MICeinto a multi-step procedure that allows the identification of relationships of various degrees of complexity. MICtools calculates their strength assessing statistical significance using a permutation-based strategy. The performances of the proposed approach are assessed by an extensive investigation in synthetic datasets and an example of a potential application on a metagenomic dataset is also illustrated.ConclusionsWe show that MICtools, combining TICeand MICe, is able to highlight associations that would not be captured by conventional strategies. MICtools is implemented in Python, and is available for download athttps://github.com/minepy/mictools.

scholarly journals Cleaning up the record on the maximal information coefficient and equitability

2014 ◽  
Vol 111 (33) ◽  
pp. E3362-E3363 ◽  
Author(s):  
D. N. Reshef ◽  
Y. A. Reshef ◽  
M. Mitzenmacher ◽  
P. C. Sabeti
Keyword(s):  
Information Coefficient ◽  
Maximal Information Coefficient

Resolution dependence of the maximal information coefficient for noiseless relationship

2013 ◽  
Vol 24 (5) ◽  
pp. 845-852 ◽  
Author(s):  
Shih-Chang Lee ◽  
Ning-Ning Pang ◽  
Wen-Jer Tzeng
Keyword(s):  
Information Coefficient ◽  
Maximal Information Coefficient

scholarly journals Analysis of generic coupling between EEG activity and PETCO2 in free breathing and breath-hold tasks using Maximal Information Coefficient (MIC)

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Maria Sole Morelli ◽  
Alberto Greco ◽  
Gaetano Valenza ◽  
Alberto Giannoni ◽  
Michele Emdin ◽  
...  
Keyword(s):  
Free Breathing ◽  
Breath Hold ◽  
Eeg Activity ◽  
Information Coefficient ◽  
Maximal Information Coefficient
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