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Combining controls can improve power in two-stage association studies.
Liley, James.
Afiliación
  • Liley J; Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK. ajl88@medschl.cam.ac.uk.
BMC Genet ; 19(1): 89, 2018 10 03.
Article en En | MEDLINE | ID: mdl-30285617
ABSTRACT

BACKGROUND:

High dimensional case control studies are ubiquitous in the biological sciences, particularly genomics. To maximise power while constraining cost and to minimise type-1 error rates, researchers typically seek to replicate findings in a second experiment on independent cohorts before proceeding with further analyses. This can be an expensive procedure, particularly when control samples are difficult to recruit or ascertain; for example in inter-disease comparisons, or studies on degenerative diseases.

RESULTS:

This paper presents a method in which control (or case) samples from the discovery cohort are re-used in a replication study. The theoretical implications of this method are discussed and simulated genome-wide association study (GWAS) tests are used to compare performance against the standard approach in a range of circumstances. Using similar methods, a procedure is proposed for 'partial replication' using a new independent cohort consisting of only controls. This methods can be used to provide some validation of findings when a full replication procedure is not possible. The new method has differing sensitivity to confounding in study cohorts compared to the standard procedure, which must be considered in its application. Type-1 error rates in these scenarios are analytically and empirically derived, and an online tool for comparing power and error rates is provided.

CONCLUSIONS:

In several common study designs, a shared-control method allows a substantial improvement in power while retaining type-1 error rate control. Although careful consideration must be made of all necessary assumptions, this method can enable more efficient use of data in GWAS and other applications.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Modelos Estadísticos / Estudio de Asociación del Genoma Completo Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: BMC Genet Asunto de la revista: BIOLOGIA MOLECULAR / BIOTECNOLOGIA Año: 2018 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Modelos Estadísticos / Estudio de Asociación del Genoma Completo Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: BMC Genet Asunto de la revista: BIOLOGIA MOLECULAR / BIOTECNOLOGIA Año: 2018 Tipo del documento: Article