TATES: efficient multivariate genotype-phenotype analysis for genome-wide association studies

PLoS Genet. 2013;9(1):e1003235. doi: 10.1371/journal.pgen.1003235. Epub 2013 Jan 24.


To date, the genome-wide association study (GWAS) is the primary tool to identify genetic variants that cause phenotypic variation. As GWAS analyses are generally univariate in nature, multivariate phenotypic information is usually reduced to a single composite score. This practice often results in loss of statistical power to detect causal variants. Multivariate genotype-phenotype methods do exist but attain maximal power only in special circumstances. Here, we present a new multivariate method that we refer to as TATES (Trait-based Association Test that uses Extended Simes procedure), inspired by the GATES procedure proposed by Li et al (2011). For each component of a multivariate trait, TATES combines p-values obtained in standard univariate GWAS to acquire one trait-based p-value, while correcting for correlations between components. Extensive simulations, probing a wide variety of genotype-phenotype models, show that TATES's false positive rate is correct, and that TATES's statistical power to detect causal variants explaining 0.5% of the variance can be 2.5-9 times higher than the power of univariate tests based on composite scores and 1.5-2 times higher than the power of the standard MANOVA. Unlike other multivariate methods, TATES detects both genetic variants that are common to multiple phenotypes and genetic variants that are specific to a single phenotype, i.e. TATES provides a more complete view of the genetic architecture of complex traits. As the actual causal genotype-phenotype model is usually unknown and probably phenotypically and genetically complex, TATES, available as an open source program, constitutes a powerful new multivariate strategy that allows researchers to identify novel causal variants, while the complexity of traits is no longer a limiting factor.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computer Simulation
  • Genetic Association Studies*
  • Genome-Wide Association Study*
  • Humans
  • Models, Genetic
  • Multivariate Analysis*
  • Polymorphism, Single Nucleotide
  • Software

Grants and funding

SvdS (VENI-451-08-025) and DP (VIDI-016-065-318) are financially supported by the Netherlands Scientific Organization (Nederlandse Organisatie voor Wetenschappelijk Onderzoek, gebied Maatschappij-en Gedragswetenschappen: NWO/MaGW). Simulations were carried out on the Genetic Cluster Computer, which is financially supported by an NWO Medium Investment grant (480-05-003); by the VU University, Amsterdam, The Netherlands; and by the Dutch Brain Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.