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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...
Autores principales: | Ganjgahi, Habib, Winkler, Anderson M., Glahn, David C., Blangero, John, Donohue, Brian, Kochunov, Peter, Nichols, Thomas E. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
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 |
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