A Bayesian Method to Incorporate Hundreds of Functional Characteristics with Association Evidence to Improve Variant Prioritization

The increasing quantity and quality of functional genomic information motivate the assessment and integration of these data with association data, including data originating from genome-wide association studies (GWAS). We used previously described GWAS signals (“hits”) to train a regularized logisti...

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Detalles Bibliográficos
Autores principales: Gagliano, Sarah A., Barnes, Michael R., Weale, Michael E., Knight, Jo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4028284/
https://www.ncbi.nlm.nih.gov/pubmed/24844982
http://dx.doi.org/10.1371/journal.pone.0098122

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4028284/
https://www.ncbi.nlm.nih.gov/pubmed/24844982
http://dx.doi.org/10.1371/journal.pone.0098122

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