A Framework for Efficient N-Way Interaction Testing in Case/Control Studies With Categorical Data

A Framework for Efficient N-Way Interaction Testing in Case/Control Studies With Categorical Data

<italic>Goal:</italic> Most common diseases are influenced by multiple gene interactions and interactions with the environment. Performing an exhaustive search to identify such interactions is computationally expensive and needs to address the multiple testing problem. A four-step framew...

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Bibliographic Details
Main Authors: Aristos Aristodimou, Athos Antoniades, Efthimios Dardiotis, Eleni Loizidou, George Spyrou, Christina Votsi, Christodoulou Kyproula, Marios Pantzaris, Nikolaos Grigoriadis, Georgios Hadjigeorgiou, Theodoros Kyriakides, Constantinos Pattichi
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Open Journal of Engineering in Medicine and Biology
Subjects:
Clustering
Epistasis
Feature Selection
Interaction Testing
Machine Learning
Online Access:https://ieeexplore.ieee.org/document/9497700/

Internet

https://ieeexplore.ieee.org/document/9497700/

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