IDEAS home Printed from https://ideas.repec.org/a/eee/thpobi/v154y2023icp94-101.html
   My bibliography  Save this article

Estimating the Lambda measure in multiple-merger coalescents

Author

Listed:
  • Miró Pina, Verónica
  • Joly, Émilien
  • Siri-Jégousse, Arno

Abstract

Multiple-merger coalescents, also known as Λ-coalescents, have been used to describe the genealogy of populations that have a skewed offspring distribution or that undergo strong selection. Inferring the characteristic measure Λ, which describes the rates of the multiple-merger events, is key to understand these processes. So far, most inference methods only work for some particular families of Λ-coalescents that are described by only one parameter, but not for more general models. This article is devoted to the construction of a non-parametric estimator of the density of Λ that is based on the observation at a single time of the so-called Site Frequency Spectrum (SFS), which describes the allelic frequencies in a present population sample. First, we produce estimates of the multiple-merger rates by solving a linear system, whose coefficients are obtained by appropriately subsampling the SFS. Then, we use a technique that aggregates the information extracted from the previous step through a kernel type of re-construction to give a non-parametric estimation of the measure Λ. We give a consistency result of this estimator under mild conditions on the behavior of Λ around 0. We also show some numerical examples of how our method performs.

Suggested Citation

  • Miró Pina, Verónica & Joly, Émilien & Siri-Jégousse, Arno, 2023. "Estimating the Lambda measure in multiple-merger coalescents," Theoretical Population Biology, Elsevier, vol. 154(C), pages 94-101.
  • Handle: RePEc:eee:thpobi:v:154:y:2023:i:c:p:94-101
    DOI: 10.1016/j.tpb.2023.09.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040580923000618
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tpb.2023.09.002?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. Freund, Fabian & Siri-Jégousse, Arno, 2021. "The impact of genetic diversity statistics on model selection between coalescents," Computational Statistics & Data Analysis, Elsevier, vol. 156(C).
    2. Schweinsberg, Jason, 2003. "Coalescent processes obtained from supercritical Galton-Watson processes," Stochastic Processes and their Applications, Elsevier, vol. 106(1), pages 107-139, July.
    3. Jerome Kelleher & Alison M Etheridge & Gilean McVean, 2016. "Efficient Coalescent Simulation and Genealogical Analysis for Large Sample Sizes," PLOS Computational Biology, Public Library of Science, vol. 12(5), pages 1-22, May.
    4. Hobolth, Asger & Siri-Jégousse, Arno & Bladt, Mogens, 2019. "Phase-type distributions in population genetics," Theoretical Population Biology, Elsevier, vol. 127(C), pages 16-32.
    5. Blath, Jochen & Cronjäger, Mathias Christensen & Eldon, Bjarki & Hammer, Matthias, 2016. "The site-frequency spectrum associated with Ξ-coalescents," Theoretical Population Biology, Elsevier, vol. 110(C), pages 36-50.
    6. Sainudiin, Raazesh & Véber, Amandine, 2018. "Full likelihood inference from the site frequency spectrum based on the optimal tree resolution," Theoretical Population Biology, Elsevier, vol. 124(C), pages 1-15.
    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. Freund, Fabian & Siri-Jégousse, Arno, 2021. "The impact of genetic diversity statistics on model selection between coalescents," Computational Statistics & Data Analysis, Elsevier, vol. 156(C).
    2. Eldon, Bjarki & Stephan, Wolfgang, 2018. "Evolution of highly fecund haploid populations," Theoretical Population Biology, Elsevier, vol. 119(C), pages 48-56.
    3. Riccardo De Bin & Vegard Grødem Stikbakke, 2023. "A boosting first-hitting-time model for survival analysis in high-dimensional settings," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(2), pages 420-440, April.
    4. Huillet, Thierry & Möhle, Martin, 2013. "On the extended Moran model and its relation to coalescents with multiple collisions," Theoretical Population Biology, Elsevier, vol. 87(C), pages 5-14.
    5. Ralph, Peter L., 2019. "An empirical approach to demographic inference with genomic data," Theoretical Population Biology, Elsevier, vol. 127(C), pages 91-101.
    6. Legried, Brandon & Terhorst, Jonathan, 2022. "Rates of convergence in the two-island and isolation-with-migration models," Theoretical Population Biology, Elsevier, vol. 147(C), pages 16-27.
    7. Zihao Wang & Wenxi Wang & Xiaoming Xie & Yongfa Wang & Zhengzhao Yang & Huiru Peng & Mingming Xin & Yingyin Yao & Zhaorong Hu & Jie Liu & Zhenqi Su & Chaojie Xie & Baoyun Li & Zhongfu Ni & Qixin Sun &, 2022. "Dispersed emergence and protracted domestication of polyploid wheat uncovered by mosaic ancestral haploblock inference," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    8. Ali Mahmoudi & Jere Koskela & Jerome Kelleher & Yao-ban Chan & David Balding, 2022. "Bayesian inference of ancestral recombination graphs," PLOS Computational Biology, Public Library of Science, vol. 18(3), pages 1-15, March.
    9. Blath, Jochen & Buzzoni, Eugenio & Koskela, Jere & Wilke Berenguer, Maite, 2020. "Statistical tools for seed bank detection," Theoretical Population Biology, Elsevier, vol. 132(C), pages 1-15.
    10. Hadzibeganovic, Tarik & Liu, Chao & Li, Rong, 2021. "Effects of reproductive skew on the evolution of ethnocentrism in structured populations with variable size," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 568(C).
    11. Parul Johri & Wolfgang Stephan & Jeffrey D Jensen, 2022. "Soft selective sweeps: Addressing new definitions, evaluating competing models, and interpreting empirical outliers," PLOS Genetics, Public Library of Science, vol. 18(2), pages 1-12, February.
    12. Simone Rubinacci & Olivier Delaneau & Jonathan Marchini, 2020. "Genotype imputation using the Positional Burrows Wheeler Transform," PLOS Genetics, Public Library of Science, vol. 16(11), pages 1-19, November.
    13. González Casanova, Adrián & Kurt, Noemi & Wakolbinger, Anton & Yuan, Linglong, 2016. "An individual-based model for the Lenski experiment, and the deceleration of the relative fitness," Stochastic Processes and their Applications, Elsevier, vol. 126(8), pages 2211-2252.
    14. Etheridge, Alison M. & Griffiths, Robert C. & Taylor, Jesse E., 2010. "A coalescent dual process in a Moran model with genic selection, and the lambda coalescent limit," Theoretical Population Biology, Elsevier, vol. 78(2), pages 77-92.
    15. Abraham, Romain & Delmas, Jean-François & He, Hui, 2021. "Some properties of stationary continuous state branching processes," Stochastic Processes and their Applications, Elsevier, vol. 141(C), pages 309-343.
    16. Möhle, Martin, 2024. "On multi-type Cannings models and multi-type exchangeable coalescents," Theoretical Population Biology, Elsevier, vol. 156(C), pages 103-116.
    17. Deng, Yun & Song, Yun S. & Nielsen, Rasmus, 2021. "The distribution of waiting distances in ancestral recombination graphs," Theoretical Population Biology, Elsevier, vol. 141(C), pages 34-43.
    18. Dhersin, Jean-Stéphane & Freund, Fabian & Siri-Jégousse, Arno & Yuan, Linglong, 2013. "On the length of an external branch in the Beta-coalescent," Stochastic Processes and their Applications, Elsevier, vol. 123(5), pages 1691-1715.
    19. Eldon, Bjarki, 2011. "Estimation of parameters in large offspring number models and ratios of coalescence times," Theoretical Population Biology, Elsevier, vol. 80(1), pages 16-28.
    20. Sergio F. Nigenda-Morales & Meixi Lin & Paulina G. Nuñez-Valencia & Christopher C. Kyriazis & Annabel C. Beichman & Jacqueline A. Robinson & Aaron P. Ragsdale & Jorge Urbán R. & Frederick I. Archer & , 2023. "The genomic footprint of whaling and isolation in fin whale populations," Nature Communications, Nature, vol. 14(1), pages 1-18, December.

    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:eee:thpobi:v:154:y:2023:i:c:p:94-101. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/intelligence .

    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.