Authors
Helena Brunel, Joan-Josep Gallardo-Chacón, Alfonso Buil, Montserrat Vallverdú, José Manuel Soria, Pere Caminal, Alexandre Perera
Publication date
2010/8/1
Journal
Bioinformatics
Volume
26
Issue
15
Pages
1811-1818
Publisher
Oxford University Press
Description
Motivation: Finding association between genetic variants and phenotypes related to disease has become an important vehicle for the study of complex disorders. In this context, multi-loci genetic association might unravel additional information when compared with single loci search. The main goal of this work is to propose a non-linear methodology based on information theory for finding combinatorial association between multi-SNPs and a given phenotype.
Results: The proposed methodology, called MISS (mutual information statistical significance), has been integrated jointly with a feature selection algorithm and has been tested on a synthetic dataset with a controlled phenotype and in the particular case of the F7 gene. The MISS methodology has been contrasted with a multiple linear regression (MLR) method used for genetic association in both, a population-based study and a sib-pairs …
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