False discovery rate control in genome-wide association studies with population structure

We present a comprehensive statistical framework to analyze data from genome-wide association studies of polygenic traits, producing interpretable findings while controlling the false discovery rate. In contrast with standard approaches, our method can leverage sophisticated multivariate algorithms...

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Detalles Bibliográficos
Autores principales: Sesia, Matteo, Bates, Stephen, Candès, Emmanuel, Marchini, Jonathan, Sabatti, Chiara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2021
Materias:
Physical Sciences
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8501795/
https://www.ncbi.nlm.nih.gov/pubmed/34580220
http://dx.doi.org/10.1073/pnas.2105841118

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8501795/
https://www.ncbi.nlm.nih.gov/pubmed/34580220
http://dx.doi.org/10.1073/pnas.2105841118

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