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BAM: A Block-Based Bayesian Method for Detecting Genome-Wide Associations with Multiple Diseases
Article proposes a novel Bayesian method, named BAM, for simultaneously partitioning Single Nucleotide Polymorphisms (SNPs) into Linkage Disequilibrium(LD)-blocks and detecting genome-wide multi-locus epistatic interactions that are associated with multiple diseases. Experimental results on the simulated datasets demonstrate that BAM is powerful and efficient.
Date:
April 16, 2020
Creator:
Guo, Xuan; Wu, Guanying & Xu, Baohua
System:
The UNT Digital Library