A Bayesian Framework for Generalized Linear Mixed Modeling Identifies New Candidate Loci for Late-Onset Alzheimer’s Disease

Recent technical and methodological advances have greatly enhanced genome-wide association studies (GWAS). The advent of low-cost, whole-genome sequencing facilitates high-resolution variant identification, and the development of linear mixed models (LMM) allows improved identification of putatively...

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Detalles Bibliográficos
Autores principales: Wang, Xulong, Philip, Vivek M., Ananda, Guruprasad, White, Charles C., Malhotra, Ankit, Michalski, Paul J., Karuturi, Krishna R. Murthy, Chintalapudi, Sumana R., Acklin, Casey, Sasner, Michael, Bennett, David A., De Jager, Philip L., Howell, Gareth R., Carter, Gregory W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Genetics Society of America 2018
Materias:
Investigations
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5937180/
https://www.ncbi.nlm.nih.gov/pubmed/29507048
http://dx.doi.org/10.1534/genetics.117.300673

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5937180/
https://www.ncbi.nlm.nih.gov/pubmed/29507048
http://dx.doi.org/10.1534/genetics.117.300673

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