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

Genome-wide association studies (GWAS) of neuroimaging data pose a significant computational burden because of the need to correct for multiple testing in both the genetic and the imaging data. Here, Ganjgahi et al. develop WLS-REML which significantly reduces computation running times in brain imag...

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Autores principales:	Habib Ganjgahi, Anderson M. Winkler, David C. Glahn, John Blangero, Brian Donohue, Peter Kochunov, Thomas E. Nichols
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/3315ced0f5074d3a9344c50e4a584c44
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spelling	oai:doaj.org-article:3315ced0f5074d3a9344c50e4a584c442021-12-02T15:33:56ZFast and powerful genome wide association of dense genetic data with high dimensional imaging phenotypes10.1038/s41467-018-05444-62041-1723https://doaj.org/article/3315ced0f5074d3a9344c50e4a584c442018-08-01T00:00:00Zhttps://doi.org/10.1038/s41467-018-05444-6https://doaj.org/toc/2041-1723Genome-wide association studies (GWAS) of neuroimaging data pose a significant computational burden because of the need to correct for multiple testing in both the genetic and the imaging data. Here, Ganjgahi et al. develop WLS-REML which significantly reduces computation running times in brain imaging GWAS.Habib GanjgahiAnderson M. WinklerDavid C. GlahnJohn BlangeroBrian DonohuePeter KochunovThomas E. NicholsNature PortfolioarticleScienceQENNature Communications, Vol 9, Iss 1, Pp 1-13 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Habib Ganjgahi Anderson M. Winkler David C. Glahn John Blangero Brian Donohue Peter Kochunov Thomas E. Nichols Fast and powerful genome wide association of dense genetic data with high dimensional imaging phenotypes
description	Genome-wide association studies (GWAS) of neuroimaging data pose a significant computational burden because of the need to correct for multiple testing in both the genetic and the imaging data. Here, Ganjgahi et al. develop WLS-REML which significantly reduces computation running times in brain imaging GWAS.
format	article
author	Habib Ganjgahi Anderson M. Winkler David C. Glahn John Blangero Brian Donohue Peter Kochunov Thomas E. Nichols
author_facet	Habib Ganjgahi Anderson M. Winkler David C. Glahn John Blangero Brian Donohue Peter Kochunov Thomas E. Nichols
author_sort	Habib Ganjgahi
title	Fast and powerful genome wide association of dense genetic data with high dimensional imaging phenotypes
title_short	Fast and powerful genome wide association of dense genetic data with high dimensional imaging phenotypes
title_full	Fast and powerful genome wide association of dense genetic data with high dimensional imaging phenotypes
title_fullStr	Fast and powerful genome wide association of dense genetic data with high dimensional imaging phenotypes
title_full_unstemmed	Fast and powerful genome wide association of dense genetic data with high dimensional imaging phenotypes
title_sort	fast and powerful genome wide association of dense genetic data with high dimensional imaging phenotypes
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/3315ced0f5074d3a9344c50e4a584c44
work_keys_str_mv	AT habibganjgahi fastandpowerfulgenomewideassociationofdensegeneticdatawithhighdimensionalimagingphenotypes AT andersonmwinkler fastandpowerfulgenomewideassociationofdensegeneticdatawithhighdimensionalimagingphenotypes AT davidcglahn fastandpowerfulgenomewideassociationofdensegeneticdatawithhighdimensionalimagingphenotypes AT johnblangero fastandpowerfulgenomewideassociationofdensegeneticdatawithhighdimensionalimagingphenotypes AT briandonohue fastandpowerfulgenomewideassociationofdensegeneticdatawithhighdimensionalimagingphenotypes AT peterkochunov fastandpowerfulgenomewideassociationofdensegeneticdatawithhighdimensionalimagingphenotypes AT thomasenichols fastandpowerfulgenomewideassociationofdensegeneticdatawithhighdimensionalimagingphenotypes
_version_	1718386952846180352

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

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