An information-gain approach to detecting three-way epistatic interactions in genetic association studies

Autor: Hu, Ting, Chen, Yuanzhu, Kiralis, Jeff W, Collins, Ryan L, Wejse, Christian, Sirugo, Giorgio, Williams, Scott M, Moore, Jason H

Publikováno v: Hu, T, Chen, Y, Kiralis, J W, Collins, R L, Wejse, C, Sirugo, G, Williams, S M & Moore, J H 2013, ' An information-gain approach to detecting three-way epistatic interactions in genetic association studies ', Journal of the American Medical Informatics Association, vol. 20, no. 4 . https://doi.org/10.1136/amiajnl-2012-001525

Background Epistasis has been historically used todescribe the phenomenon that the effect of a givengene on a phenotype can be dependent on one or moreother genes, and is an essential element forunderstanding the association between genetic andphenot

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https://pure.au.dk/portal/da/publications/an-informationgain-approach-to-detecting-threeway-epistatic-interactions-in-genetic-association-studies(777f5ec8-dea8-4abc-9c0b-3f22ae0afd80).html

An information-gain approach to detecting three-way epistatic interactions in genetic association studies.

Autor: Ting Hu^1,2, Yuanzhu Chen^1,3, Kiralis, Jeff W.¹, Collins, Ryan L.¹, Wejse, Christian⁴, Sirugo, Giorgio⁵, Williams, Scott M.², Moore, Jason H.^1,2 Jason.h.moore@dartmouth.edu

Publikováno v: Journal of the American Medical Informatics Association. Jul2013, Vol. 20 Issue 4, p630-636. 7p. 3 Diagrams, 1 Chart, 2 Graphs.

Vi SEN: Methodology and Software for Visualization of Statistical Epistasis Networks.

Autor: Hu, Ting, Chen, Yuanzhu, Kiralis, Jeff W., Moore, Jason H.

Publikováno v: Genetic Epidemiology; Apr2013, Vol. 37 Issue 3, p283-285, 3p