Explaining the Genetic Causality for Complex Phenotype via Deep Association Kernel Learning

Explaining the Genetic Causality for Complex Phenotype via Deep Association Kernel Learning

Summary: The genetic effect explains the causality from genetic mutations to the development of complex diseases. Existing genome-wide association study (GWAS) approaches are always built under a linear assumption, restricting their generalization in dissecting complicated causality such as the rece...

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Bibliographic Details
Main Authors: Feng Bao, Yue Deng, Mulong Du, Zhiquan Ren, Sen Wan, Kenny Ye Liang, Shaohua Liu, Bo Wang, Junyi Xin, Feng Chen, David C. Christiani, Meilin Wang, Qionghai Dai
Format: Article
Language:English
Published: Elsevier 2020-09-01
Series:Patterns
Subjects:
kernel learning
association analysis
deep learning
genome-wide association studies
disease causality
Online Access:http://www.sciencedirect.com/science/article/pii/S2666389920300684

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http://www.sciencedirect.com/science/article/pii/S2666389920300684

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