Bayesian reassessment of the epigenetic architecture of complex traits

Bayesian reassessment of the epigenetic architecture of complex traits

Linking epigenetic marks to clinical outcomes promises insight into the underlying processes. Here, the authors introduce a statistical approach to estimate associations between a phenotype and all epigenetic probes jointly, and to estimate the proportion of variation captured by epigenetic effects.

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Detalles Bibliográficos
Autores principales: Daniel Trejo Banos, Daniel L. McCartney, Marion Patxot, Lucas Anchieri, Thomas Battram, Colette Christiansen, Ricardo Costeira, Rosie M. Walker, Stewart W. Morris, Archie Campbell, Qian Zhang, David J. Porteous, Allan F. McRae, Naomi R. Wray, Peter M. Visscher, Chris S. Haley, Kathryn L. Evans, Ian J. Deary, Andrew M. McIntosh, Gibran Hemani, Jordana T. Bell, Riccardo E. Marioni, Matthew R. Robinson
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
Materias:
Science
Q
Acceso en línea:https://doaj.org/article/74bbcbe2232d46d983d1a26fad579404
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Descripción
Sumario:Linking epigenetic marks to clinical outcomes promises insight into the underlying processes. Here, the authors introduce a statistical approach to estimate associations between a phenotype and all epigenetic probes jointly, and to estimate the proportion of variation captured by epigenetic effects.

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