Fast and powerful genome wide association of dense genetic data with high dimensional imaging phenotypes

Genome wide association (GWA) analysis of brain imaging phenotypes can advance our understanding of the genetic basis of normal and disorder-related variation in the brain. GWA approaches typically use linear mixed effect models to account for non-independence amongst subjects due to factors, such a...

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Detalles Bibliográficos
Autores principales: Ganjgahi, Habib, Winkler, Anderson M., Glahn, David C., Blangero, John, Donohue, Brian, Kochunov, Peter, Nichols, Thomas E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6092439/
https://www.ncbi.nlm.nih.gov/pubmed/30108209
http://dx.doi.org/10.1038/s41467-018-05444-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6092439/
https://www.ncbi.nlm.nih.gov/pubmed/30108209
http://dx.doi.org/10.1038/s41467-018-05444-6

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