J Am Med Inform Assoc - An information-gain approach to detecting three-way epistatic interactions in genetic association studies.

Tópicos

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Resumo

CKGROUND: Epistasis has been historically used to describe the phenomenon that the effect of a given gene on a phenotype can be dependent on one or more other genes, and is an essential element for understanding the association between genetic and phenotypic variations. Quantifying epistasis of orders higher than two is very challenging due to both the computational complexity of enumerating all possible combinations in genome-wide data and the lack of efficient and effective methodologies.OBJECTIVES: In this study, we propose a fast, non-parametric, and model-free measure for three-way epistasis.METHODS: Such a measure is based on information gain, and is able to separate all lower order effects from pure three-way epistasis.RESULTS: Our method was verified on synthetic data and applied to real data from a candidate-gene study of tuberculosis in a West African population. In the tuberculosis data, we found a statistically significant pure three-way epistatic interaction effect that was stronger than any lower-order associations.CONCLUSION: Our study provides a methodological basis for detecting and characterizing high-order gene-gene interactions in genetic association studies.

Resumo Limpo

ckground epistasi histor use describ phenomenon effect given gene phenotyp can depend one gene essenti element understand associ genet phenotyp variat quantifi epistasi order higher two challeng due comput complex enumer possibl combin genomewid data lack effici effect methodologiesobject studi propos fast nonparametr modelfre measur threeway epistasismethod measur base inform gain abl separ lower order effect pure threeway epistasisresult method verifi synthet data appli real data candidategen studi tuberculosi west african popul tuberculosi data found statist signific pure threeway epistat interact effect stronger lowerord associationsconclus studi provid methodolog basi detect character highord genegen interact genet associ studi

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