A Two-Stage Mutual Information Based Bayesian Lasso Algorithm for Multi-Locus Genome-Wide Association Studies

A Two-Stage Mutual Information Based Bayesian Lasso Algorithm for Multi-Locus Genome-Wide Association Studies

Genome-wide association study (GWAS) has turned out to be an essential technology for exploring the genetic mechanism of complex traits. To reduce the complexity of computation, it is well accepted to remove unrelated single nucleotide polymorphisms (SNPs) before GWAS, e.g., by using iterative sure...

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Bibliographic Details
Main Authors: Hongping Guo, Zuguo Yu, Jiyuan An, Guosheng Han, Yuanlin Ma, Runbin Tang
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Entropy
Subjects:
gwas
pearson correlation
mutual information
feature screening
bayesian lasso
Online Access:https://www.mdpi.com/1099-4300/22/3/329

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https://www.mdpi.com/1099-4300/22/3/329

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