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Multidimensional Scaling and Relatedness Research

Jan Graffelman, Iván Galván Femenía, Rafael de Cid, Carles Barceló-i-Vidal
doi: https://doi.org/10.1101/297879
Jan Graffelman
1Department of Statistics and Operations Research Universitat Politècnica de Catalunya, Barcelona, Spain
2Department of Biostatistics University of Washington, Seattle, USA
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Iván Galván Femenía
3Department of Computer Science, Applied Mathematics & Statistics Universitat de Girona, Girona, Spain
4Genomes For Life - GCAT lab Program of Predictive and Personalized Medicine of Cancer (PMPPC) Institute for Health Science Research Germans Trias i Pujol (IGTP) Can Ruti Campus, Badalona, Barcelona, Spain
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Rafael de Cid
4Genomes For Life - GCAT lab Program of Predictive and Personalized Medicine of Cancer (PMPPC) Institute for Health Science Research Germans Trias i Pujol (IGTP) Can Ruti Campus, Badalona, Barcelona, Spain
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Carles Barceló-i-Vidal
3Department of Computer Science, Applied Mathematics & Statistics Universitat de Girona, Girona, Spain
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Abstract

Multidimensional scaling is a well-known multivariate technique, that is often used in genetics for studying population substructure. In this paper we show that multidimensional scaling of marker data is of relevance for relatedness research. Relatedness is usually investigated by estimating and plotting identity-by-state and identity-by-descent allele-sharing statistics. We show that outlying individuals in a map obtained by multidimensional scaling of genetic variables do not necessarily stem from a different human population, but can be the consequence of relatedness. We propose a method for classifying pairs of individuals into the standard relationship categories that combines genetic bootstrapping, multidimensional scaling and discriminant analysis. We validate our method with simulation studies. Given the variant filtering procedures, our method classifies relationships up to and including the fourth degree with high accuracy (96-97%), using only identity by state. The usefulness of the method is illustrated with data from the 1,000 genomes and the GCAT projects.

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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-ND 4.0 International license.
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Posted April 09, 2018.
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Multidimensional Scaling and Relatedness Research
Jan Graffelman, Iván Galván Femenía, Rafael de Cid, Carles Barceló-i-Vidal
bioRxiv 297879; doi: https://doi.org/10.1101/297879
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Multidimensional Scaling and Relatedness Research
Jan Graffelman, Iván Galván Femenía, Rafael de Cid, Carles Barceló-i-Vidal
bioRxiv 297879; doi: https://doi.org/10.1101/297879

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