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Article

GLOGS: a fast and powerful method for GWAS of binary traits with risk covariates in related populations.

Bioinformatics (Oxford, England) - 1 Jun 2012

Stanhope Stephen A, Abney Mark

Abstract excerpt

SUMMARY: Mixed model-based approaches to genome-wide association studies (GWAS) of binary traits in related individuals can account for non-genetic risk factors in an integrated manner. However, they are technically challenging. GLOGS (Genome-wide LOGistic mixed model/Score test) addresses such challenges with efficient statistical procedures and a parallel implementation. GLOGS has high power relative to...

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Identifiers

PMID: 22522135
DOI: 10.1093/bioinformatics/bts190
PMCID: PMC3356846

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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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