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Article

JAM: A Scalable Bayesian Framework for Joint Analysis of Marginal SNP Effects.

Genetic epidemiology - 1 Apr 2016

Newcombe Paul J, Conti David V, Richardson Sylvia

Abstract excerpt

Recently, large scale genome-wide association study (GWAS) meta-analyses have boosted the number of known signals for some traits into the tens and hundreds. Typically, however, variants are only analysed one-at-a-time. This complicates the ability of fine-mapping to identify a small set of SNPs for further functional follow-up. We describe a new and scalable algorithm, joint analysis of marginal summary...

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PMID: 27027514
DOI: 10.1002/gepi.21953
PMCID: PMC4817278

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ADCY5

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

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