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How to choose sets of ancestry informative markers: A supervised feature selection approach

Peter Pfaffelhuber, Franziska Grundner-Culemann, Veronika Lipphardt, Franz Baumdicker
doi: https://doi.org/10.1101/759464
Peter Pfaffelhuber
1University of Freiburg, Department of Mathematical Stochastics, Ernst-Zermelo-Straße 1, D - 79104 Freiburg, Germany
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  • For correspondence: p.p@stochastik.uni-freiburg.de
Franziska Grundner-Culemann
3University of Freiburg, Faculty of Medicine and Medical Center, Institute of Genetic Epidemiolo Germany
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Veronika Lipphardt
4University College Freiburg, Bertoldstraße 17, D - 79098 Freiburg, Germany
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Franz Baumdicker
1University of Freiburg, Department of Mathematical Stochastics, Ernst-Zermelo-Straße 1, D - 79104 Freiburg, Germany
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Abstract

Inference of the Biogeographical Ancestry (BGA) of a person or trace relies on three ingredients: (1) A reference database of DNA samples including BGA information; (2) a statistical clustering method; (3) a set of loci which segregate dependent on geographical location, i.e. a set of so-called Ancestry Informative Markers (AIMs). We used the theory of feature selection from statistical learning in order to obtain AIM-sets for BGA inference. Using simulations, we show that this learning procedure works in various cases, and outperforms ad hoc methods, based on statistics like FST or informativeness for the choice of AIMs. Applying our method to data from the 1000 genomes project (excluding Admixed Americans) we identified an AIMset of 17 SNPs, which partly overlaps with existing ones. For continental BGA, the AIMset outperforms existing AIMsets on the 1000 genomes dataset, and gives a vanishing misclassification error.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted September 08, 2019.
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How to choose sets of ancestry informative markers: A supervised feature selection approach
Peter Pfaffelhuber, Franziska Grundner-Culemann, Veronika Lipphardt, Franz Baumdicker
bioRxiv 759464; doi: https://doi.org/10.1101/759464
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How to choose sets of ancestry informative markers: A supervised feature selection approach
Peter Pfaffelhuber, Franziska Grundner-Culemann, Veronika Lipphardt, Franz Baumdicker
bioRxiv 759464; doi: https://doi.org/10.1101/759464

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