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Schweiger, R.* ; Fisher, E.* ; Weissbrod, O.* ; Rahmani, E.* ; Müller-Nurasyid, M. ; Kunze, S. ; Gieger, C. ; Waldenberger, M. ; Rosset, S.* ; Halperin, E.*

Detecting heritable phenotypes without a model using fast permutation testing for heritability and set-tests.

Nat. Commun. 9:4919 (2018)
Verlagsversion Forschungsdaten DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Testing for association between a set of genetic markers and a phenotype is a fundamental task in genetic studies. Standard approaches for heritability and set testing strongly rely on parametric models that make specific assumptions regarding phenotypic variability. Here, we show that resulting p-values may be inflated by up to 15 orders of magnitude, in a heritability study of methylation measurements, and in a heritability and expression quantitative trait loci analysis of gene expression profiles. We propose FEATHER, a method for fast permutation-based testing of marker sets and of heritability, which properly controls for false-positive results. FEATHER eliminated 47% of methylation sites found to be heritable by the parametric test, suggesting a substantial inflation of false-positive findings by alternative methods. Our approach can rapidly identify heritable phenotypes out of millions of phenotypes acquired via high-throughput technologies, does not suffer from model misspecification and is highly efficient.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Linear Mixed Models; Kernel Association Test; Variance-components; Gene-expression; Stochastic-approximation; Peripheral-blood; Dna Methylation; Monte-carlo; Powerful; Traits
ISSN (print) / ISBN 2041-1723
e-ISSN 2041-1723
Zeitschrift Nature Communications
Quellenangaben Band: 9, Heft: 1, Seiten: , Artikelnummer: 4919 Supplement: ,
Verlag Nature Publishing Group
Verlagsort London
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Genetic Epidemiology (IGE)
Institute of Epidemiology II (EPI2)