IDEAS home Printed from https://ideas.repec.org/a/bpj/sagmbi/v15y2016i6p473-490n1.html
   My bibliography  Save this article

Tree-based quantitative trait mapping in the presence of external covariates

Author

Listed:
  • Thompson Katherine L.

    (Department of Statistics, University of Kentucky, Lexington, KY, United States of America)

  • Linnen Catherine R.

    (Department of Biology, University of Kentucky, Lexington, KY, United States of America)

  • Kubatko Laura

    (Departments of Statistics and Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH, United States of America)

Abstract

A central goal in biological and biomedical sciences is to identify the molecular basis of variation in morphological and behavioral traits. Over the last decade, improvements in sequencing technologies coupled with the active development of association mapping methods have made it possible to link single nucleotide polymorphisms (SNPs) and quantitative traits. However, a major limitation of existing methods is that they are often unable to consider complex, but biologically-realistic, scenarios. Previous work showed that association mapping method performance can be improved by using the evolutionary history within each SNP to estimate the covariance structure among randomly-sampled individuals. Here, we propose a method that can be used to analyze a variety of data types, such as data including external covariates, while considering the evolutionary history among SNPs, providing an advantage over existing methods. Existing methods either do so at a computational cost, or fail to model these relationships altogether. By considering the broad-scale relationships among SNPs, the proposed approach is both computationally-feasible and informed by the evolutionary history among SNPs. We show that incorporating an approximate covariance structure during analysis of complex data sets increases performance in quantitative trait mapping, and apply the proposed method to deer mice data.

Suggested Citation

  • Thompson Katherine L. & Linnen Catherine R. & Kubatko Laura, 2016. "Tree-based quantitative trait mapping in the presence of external covariates," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 15(6), pages 473-490, December.
    • Handle: RePEc:bpj:sagmbi:v:15:y:2016:i:6:p:473-490:n:1
    DOI: 10.1515/sagmb-2015-0107
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/sagmb-2015-0107
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/sagmb-2015-0107?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nick Patterson & Alkes L Price & David Reich, 2006. "Population Structure and Eigenanalysis," PLOS Genetics, Public Library of Science, vol. 2(12), pages 1-20, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gyaneshwer Chaubey & Anurag Kadian & Saroj Bala & Vadlamudi Raghavendra Rao, 2015. "Genetic Affinity of the Bhil, Kol and Gond Mentioned in Epic Ramayana," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-11, June.
    2. Daniel Svensson & Matilda Rentoft & Anna M Dahlin & Emma Lundholm & Pall I Olason & Andreas Sjödin & Carin Nylander & Beatrice S Melin & Johan Trygg & Erik Johansson, 2020. "A whole-genome sequenced control population in northern Sweden reveals subregional genetic differences," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-18, September.
    3. Estavoyer, Maxime & François, Olivier, 2022. "Theoretical analysis of principal components in an umbrella model of intraspecific evolution," Theoretical Population Biology, Elsevier, vol. 148(C), pages 11-21.
    4. Felsenstein, Joseph, 2015. "Covariation of gene frequencies in a stepping-stone lattice of populations," Theoretical Population Biology, Elsevier, vol. 100(C), pages 88-97.
    5. Yaron Granot & Omri Tal & Saharon Rosset & Karl Skorecki, 2016. "On the Apportionment of Population Structure," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-24, August.
    6. Özkan İş & Xue Wang & Joseph S. Reddy & Yuhao Min & Elanur Yilmaz & Prabesh Bhattarai & Tulsi Patel & Jeremiah Bergman & Zachary Quicksall & Michael G. Heckman & Frederick Q. Tutor-New & Birsen Can De, 2024. "Gliovascular transcriptional perturbations in Alzheimer’s disease reveal molecular mechanisms of blood brain barrier dysfunction," Nature Communications, Nature, vol. 15(1), pages 1-23, December.
    7. Hyosik Jang & Ian M Ehrenreich, 2012. "Genome-Wide Characterization of Genetic Variation in the Unicellular, Green Alga Chlamydomonas reinhardtii," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-9, July.
    8. Mathieu Gautier & Denis Laloë & Katayoun Moazami-Goudarzi, 2010. "Insights into the Genetic History of French Cattle from Dense SNP Data on 47 Worldwide Breeds," PLOS ONE, Public Library of Science, vol. 5(9), pages 1-11, September.
    9. Xiaofeng Cai & Xuepeng Sun & Chenxi Xu & Honghe Sun & Xiaoli Wang & Chenhui Ge & Zhonghua Zhang & Quanxi Wang & Zhangjun Fei & Chen Jiao & Quanhua Wang, 2021. "Genomic analyses provide insights into spinach domestication and the genetic basis of agronomic traits," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    10. Lee, Anthony J. & Hibbs, Courtney & Wright, Margaret J. & Martin, Nicholas G. & Keller, Matthew C. & Zietsch, Brendan P., 2017. "Assessing the accuracy of perceptions of intelligence based on heritable facial features," Intelligence, Elsevier, vol. 64(C), pages 1-8.
    11. Matthieu Bouaziz & Caroline Paccard & Mickael Guedj & Christophe Ambroise, 2012. "SHIPS: Spectral Hierarchical Clustering for the Inference of Population Structure in Genetic Studies," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-17, October.
    12. Jacobo Pardo-Seco & Alberto Gómez-Carballa & Jorge Amigo & Federico Martinón-Torres & Antonio Salas, 2014. "A Genome-Wide Study of Modern-Day Tuscans: Revisiting Herodotus's Theory on the Origin of the Etruscans," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-11, September.
    13. Andrey V Khrunin & Denis V Khokhrin & Irina N Filippova & Tõnu Esko & Mari Nelis & Natalia A Bebyakova & Natalia L Bolotova & Janis Klovins & Liene Nikitina-Zake & Karola Rehnström & Samuli Ripatti & , 2013. "A Genome-Wide Analysis of Populations from European Russia Reveals a New Pole of Genetic Diversity in Northern Europe," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-9, March.
    14. Ilja M Nolte & Chris Wallace & Stephen J Newhouse & Daryl Waggott & Jingyuan Fu & Nicole Soranzo & Rhian Gwilliam & Panos Deloukas & Irina Savelieva & Dongling Zheng & Chrysoula Dalageorgou & Martin F, 2009. "Common Genetic Variation Near the Phospholamban Gene Is Associated with Cardiac Repolarisation: Meta-Analysis of Three Genome-Wide Association Studies," PLOS ONE, Public Library of Science, vol. 4(7), pages 1-10, July.
    15. Hoicheong Siu & Li Jin & Momiao Xiong, 2012. "Manifold Learning for Human Population Structure Studies," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-18, January.
    16. Elodie Persyn & Richard Redon & Lise Bellanger & Christian Dina, 2018. "The impact of a fine-scale population stratification on rare variant association test results," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-17, December.
    17. Andre Krumel Portella & Afroditi Papantoni & Catherine Paquet & Spencer Moore & Keri Shiels Rosch & Stewart Mostofsky & Richard S Lee & Kimberly R Smith & Robert Levitan & Patricia Pelufo Silveira & S, 2020. "Predicted DRD4 prefrontal gene expression moderates snack intake and stress perception in response to the environment in adolescents," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-20, June.
    18. Lindsay Fernández-Rhodes & Jennifer R Malinowski & Yujie Wang & Ran Tao & Nathan Pankratz & Janina M Jeff & Sachiko Yoneyama & Cara L Carty & V Wendy Setiawan & Loic Le Marchand & Christopher Haiman &, 2018. "The genetic underpinnings of variation in ages at menarche and natural menopause among women from the multi-ethnic Population Architecture using Genomics and Epidemiology (PAGE) Study: A trans-ethnic ," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-21, July.
    19. Pierre Luisi & Angelina García & Juan Manuel Berros & Josefina M B Motti & Darío A Demarchi & Emma Alfaro & Eliana Aquilano & Carina Argüelles & Sergio Avena & Graciela Bailliet & Julieta Beltramo & C, 2020. "Fine-scale genomic analyses of admixed individuals reveal unrecognized genetic ancestry components in Argentina," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-30, July.
    20. Peña-Malavera Andrea & Bruno Cecilia & Fernandez Elmer & Balzarini Monica, 2014. "Comparison of algorithms to infer genetic population structure from unlinked molecular markers," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(4), pages 391-402, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:sagmbi:v:15:y:2016:i:6:p:473-490:n:1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.