Universität zu Köln

Stephan, Johannes ORCID: 0000-0002-1279-2477, Stegle, Oliver ORCID: 0000-0002-8818-7193 and Beyer, Andreas ORCID: 0000-0002-3891-2123 (2015). A random forest approach to capture genetic effects in the presence of population structure. Nat. Commun., 6. LONDON: NATURE PUBLISHING GROUP. ISSN 2041-1723

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Abstract

The accurate mapping of causal variants in genome-wide association studies requires the consideration of both, confounding factors (for example, population structure) and nonlinear interactions between individual genetic variants. Here, we propose a method termed 'mixed random forest' that simultaneously accounts for population structure and captures nonlinear genetic effects. We test the model in simulation experiments and show that the mixed random forest approach improves detection power compared with established approaches. In an application to data from an outbred mouse population, we find that mixed random forest identifies associations that are more consistent with prior knowledge than competing methods. Further, our approach allows predicting phenotypes from genotypes with greater accuracy than any of the other methods that we tested. Our results show that approaches that simultaneously account for both, confounding due to population structure and epistatic interactions, are important to fully explain the heritable component of complex quantitative traits.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Stephan, Johannes UNSPECIFIED orcid.org/0000-0002-1279-2477 UNSPECIFIED Stegle, Oliver UNSPECIFIED orcid.org/0000-0002-8818-7193 UNSPECIFIED Beyer, Andreas UNSPECIFIED orcid.org/0000-0002-3891-2123 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-402359
DOI:	10.1038/ncomms8432
Journal or Publication Title:	Nat. Commun.
Volume:	6
Date:	2015
Publisher:	NATURE PUBLISHING GROUP
Place of Publication:	LONDON
ISSN:	2041-1723
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language QUANTITATIVE TRAIT LOCI; GENOME-WIDE ASSOCIATION; LINEAR MIXED MODELS; MISSING HERITABILITY; COMPLEX TRAITS; SELECTION; EPISTASIS; MARKER; PREDICTION; MYSTERY Multiple languages Multidisciplinary Sciences Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/40235