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Coalescence computations for large samples drawn from populations of time-varying sizes

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  • Andrzej Polanski
  • Agnieszka Szczesna
  • Mateusz Garbulowski
  • Marek Kimmel

Abstract

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.

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  • Andrzej Polanski & Agnieszka Szczesna & Mateusz Garbulowski & Marek Kimmel, 2017. "Coalescence computations for large samples drawn from populations of time-varying sizes," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-22, February.
    • Handle: RePEc:plo:pone00:0170701
    DOI: 10.1371/journal.pone.0170701
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    Cited by:

    1. Melfi, Andrew & Viswanath, Divakar, 2018. "Single and simultaneous binary mergers in Wright-Fisher genealogies," Theoretical Population Biology, Elsevier, vol. 121(C), pages 60-71.

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