Selecting likely causal risk factors from high-throughput experiments using multivariable Mendelian randomization

Multivariable Mendelian randomization (MR) extends the standard MR framework to consider multiple risk factors in a single model. Here, Zuber et al. propose MR-BMA, a Bayesian variable selection approach to identify the likely causal determinants of a disease from many candidate risk factors as for...

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Autores principales: Verena Zuber, Johanna Maria Colijn, Caroline Klaver, Stephen Burgess
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Acceso en línea:https://doaj.org/article/25ac00d0332e4bc4a929fc5680c24f8b
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