Efficient set tests for the genetic analysis of correlated traits

Nat Methods. 2015 Aug;12(8):755-8. doi: 10.1038/nmeth.3439. Epub 2015 Jun 15.

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.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Alleles
  • Animals
  • Calibration
  • Computational Biology / methods*
  • Computer Simulation
  • Data Interpretation, Statistical
  • Gene Frequency
  • Genetic Variation
  • Genome-Wide Association Study
  • Humans
  • Internet
  • Leukocytes / cytology
  • Models, Statistical
  • Phenotype
  • Polymorphism, Single Nucleotide
  • Quantitative Trait Loci
  • Rats
  • Regression Analysis
  • Reproducibility of Results
  • Software