Helmholtz Gemeinschaft


Efficient set tests for the genetic analysis of correlated traits

Item Type:Article
Title:Efficient set tests for the genetic analysis of correlated traits
Creators Name:Casale, F.P. and Rakitsch, B. and 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
Publisher:Nature Publishing Group
Page Range:755-758
Date:August 2015
Official Publication:https://doi.org/10.1038/nmeth.3439
PubMed:View item in PubMed

Repository Staff Only: item control page

Open Access
MDC Library