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Showing 1–7 of 7 results

Advanced filters: Author: Carl Kadie Clear advanced filters

FaST linear mixed models for genome-wide association studies

An algorithm for linear mixed models substantially reduces memory usage and run time for genome-wide association studies. The improved algorithm scales linearly in cohort size, allowing the application of these models to much larger samples.

Christoph Lippert
Jennifer Listgarten
David Heckerman
Research04 Sept 2011
Nature Methods

Volume: 8, P: 833-835
An Exhaustive Epistatic SNP Association Analysis on Expanded Wellcome Trust Data

Christoph Lippert
Jennifer Listgarten
David Heckerman
ResearchOpen Access22 Jan 2013
Scientific Reports

Volume: 3, P: 1-5
Improved linear mixed models for genome-wide association studies

Jennifer Listgarten
Christoph Lippert
David Heckerman
Correspondence30 May 2012
Nature Methods

Volume: 9, P: 525-526
HIV-1 adaptation to NK-cell-mediated immune pressure

Galit Alter
David Heckerman
Marcus Altfeld
Research03 Aug 2011
Nature

Volume: 476, P: 96-100
Correction: Corrigendum: An Exhaustive Epistatic SNP Association Analysis on Expanded Wellcome Trust Data

Christoph Lippert
Jennifer Listgarten
David Heckerman
Amendments and Corrections18 Feb 2013
Scientific Reports

Volume: 3, P: 1
The benefits of selecting phenotype-specific variants for applications of mixed models in genomics

Christoph Lippert
Gerald Quon
David Heckerman
ResearchOpen Access09 May 2013
Scientific Reports

Volume: 3, P: 1-9
Further Improvements to Linear Mixed Models for Genome-Wide Association Studies

Christian Widmer
Christoph Lippert
David Heckerman
ResearchOpen Access12 Nov 2014
Scientific Reports

Volume: 4, P: 1-13