Greater power and computational efficiency for kernel-based association testing of sets of genetic variants

Motivation: Set-based variance component tests have been identified as a way to increase power in association studies by aggregating weak individual effects. However, the choice of test statistic has been largely ignored even though it may play an important role in obtaining optimal power. We compar...

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Detalles Bibliográficos
Autores principales: Lippert, Christoph, Xiang, Jing, Horta, Danilo, Widmer, Christian, Kadie, Carl, Heckerman, David, Listgarten, Jennifer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Original Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4221116/
https://www.ncbi.nlm.nih.gov/pubmed/25075117
http://dx.doi.org/10.1093/bioinformatics/btu504

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4221116/
https://www.ncbi.nlm.nih.gov/pubmed/25075117
http://dx.doi.org/10.1093/bioinformatics/btu504

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