Literature DB >> 29468442

A Brief Critique of the TATES Procedure.

Fazil Aliev1,2, Jessica E Salvatore3,4, Arpana Agrawal5, Laura Almasy6, Grace Chan7, Howard J Edenberg8, Victor Hesselbrock7, Samuel Kuperman9, Jacquelyn Meyers10, Danielle M Dick11,12.   

Abstract

The Trait-based test that uses the Extended Simes procedure (TATES) was developed as a method for conducting multivariate GWAS for correlated phenotypes whose underlying genetic architecture is complex. In this paper, we provide a brief methodological critique of the TATES method using simulated examples and a mathematical proof. Our simulated examples using correlated phenotypes show that the Type I error rate is higher than expected, and that more TATES p values fall outside of the confidence interval relative to expectation. Thus the method may result in systematic inflation when used with correlated phenotypes. In a mathematical proof we further demonstrate that the distribution of TATES p values deviates from expectation in a manner indicative of inflation. Our findings indicate the need for caution when using TATES for multivariate GWAS of correlated phenotypes.

Entities:  

Keywords:  Complex traits; Multivariate GWAS; TATES

Mesh:

Year:  2018        PMID: 29468442      PMCID: PMC6028780          DOI: 10.1007/s10519-018-9890-6

Source DB:  PubMed          Journal:  Behav Genet        ISSN: 0001-8244            Impact factor:   2.805


  5 in total

1.  GATES: a rapid and powerful gene-based association test using extended Simes procedure.

Authors:  Miao-Xin Li; Hong-Sheng Gui; Johnny S H Kwan; Pak C Sham
Journal:  Am J Hum Genet       Date:  2011-03-11       Impact factor: 11.025

2.  A comparison of multivariate genome-wide association methods.

Authors:  Tessel E Galesloot; Kristel van Steen; Lambertus A L M Kiemeney; Luc L Janss; Sita H Vermeulen
Journal:  PLoS One       Date:  2014-04-24       Impact factor: 3.240

3.  An efficient genome-wide association test for multivariate phenotypes based on the Fisher combination function.

Authors:  James J Yang; Jia Li; L Keoki Williams; Anne Buu
Journal:  BMC Bioinformatics       Date:  2016-01-05       Impact factor: 3.169

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

Authors:  Sophie van der Sluis; Danielle Posthuma; Conor V Dolan
Journal:  PLoS Genet       Date:  2013-01-24       Impact factor: 5.917

5.  Do baseline P-values follow a uniform distribution in randomised trials?

Authors:  Martin Bland
Journal:  PLoS One       Date:  2013-10-01       Impact factor: 3.240

  5 in total

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