Efficient set tests for the genetic analysis of correlated traits

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Item Type:	Article
Title:	Efficient set tests for the genetic analysis of correlated traits
Creators Name:	Casale, F.P., Rakitsch, B., Lippert, C. and Stegle, O.
Abstract:	Set tests are a powerful approach for genome-wide association testing between groups of genetic variants and quantitative traits. We describe mtSet (http://github.com/PMBio/limix), a mixed-model approach that enables joint analysis across multiple correlated traits while accounting for population structure and relatedness. mtSet effectively combines the benefits of set tests with multi-trait modeling and is computationally efficient, enabling genetic analysis of large cohorts (up to 500,000 individuals) and multiple traits.
Keywords:	Algorithms, Alleles, Calibration, Computational Biology, Computer Simulation, Gene Frequency, Genetic Variation, Genome-Wide Association Study, Internet, Leukocytes, Phenotype, Quantitative Trait Loci, Regression Analysis, Reproducibility of Results, Single Nucleotide Polymorphism, Software, Statistical Data Interpretation, Statistical Models, Animals, Rats
Source:	Nature Methods
ISSN:	1548-7091
Publisher:	Nature Publishing Group
Volume:	12
Number:	8
Page Range:	755-758
Date:	August 2015
Official Publication:	https://doi.org/10.1038/nmeth.3439
PubMed:	View item in PubMed

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