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Article

Bayesian GWAS with Structured and Non-Local Priors.

Bioinformatics (Oxford, England) - 1 Jan 2020

Kaplan Adam, Lock Eric F, Fiecas Mark

Abstract excerpt

MOTIVATION: The flexibility of a Bayesian framework is promising for GWAS, but current approaches can benefit from more informative prior models. We introduce a novel Bayesian approach to GWAS, called Structured and Non-Local Priors (SNLPs) GWAS, that improves over existing methods in two important ways. First, we describe a model that allows for a marker's gene-parent membership and other characteristics to...

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Identifiers

PMID: 31651034
DOI: 10.1093/bioinformatics/btz518
PMCID: PMC6956774

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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