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Coalescence computations for large samples drawn from populations of time-varying sizes
Silesian Tech Univ, Inst Informat, Ul Akad 16, PL-44100 Gliwice, Poland..
Silesian Tech Univ, Inst Informat, Ul Akad 16, PL-44100 Gliwice, Poland..
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Silesian Tech Univ, Inst Informat, Ul Akad 16, PL-44100 Gliwice, Poland..
Silesian Tech Univ, Syst Engn Grp, Ul Akad 16, PL-44100 Gliwice, Poland.;Rice Univ, Dept Stat, MS 138,6100 Main St, Houston, TX 77005 USA..
2017 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 12, no 2, e0170701Article in journal (Refereed) Published
Abstract [en]

We present new results concerning probability distributions of times in the coalescence tree and expected allele frequencies for coalescent with large sample size. The obtained results are based on computational methodologies, which involve combining coalescence time scale changes with techniques of integral transformations and using analytical formulae for infinite products. We show applications of the proposed methodologies for computing probability distributions of times in the coalescence tree and their limits, for evaluation of accuracy of approximate expressions for times in the coalescence tree and expected allele frequencies, and for analysis of large human mitochondrial DNA dataset.

Place, publisher, year, edition, pages
2017. Vol. 12, no 2, e0170701
National Category
Biological Sciences
Identifiers
URN: urn:nbn:se:uu:diva-317952DOI: 10.1371/journal.pone.0170701ISI: 000393705500009PubMedID: 28170404OAI: oai:DiVA.org:uu-317952DiVA: diva2:1086337
Available from: 2017-04-01 Created: 2017-04-01 Last updated: 2017-04-01Bibliographically approved

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