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The coalescent of a sample from a binary branching process

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  • Lambert, Amaury

Abstract

At time 0, start a time-continuous binary branching process, where particles give birth to a single particle independently (at a possibly time-dependent rate) and die independently (at a possibly time-dependent and age-dependent rate). A particular case is the classical birth–death process. Stop this process at time T>0. It is known that the tree spanned by the N tips alive at time T of the tree thus obtained (called a reduced tree or coalescent tree) is a coalescent point process (CPP), which basically means that the depths of interior nodes are independent and identically distributed (iid). Now select each of the N tips independently with probability y (Bernoulli sample). It is known that the tree generated by the selected tips, which we will call the Bernoulli sampled CPP, is again a CPP. Now instead, select exactly k tips uniformly at random among the N tips (a k-sample). We show that the tree generated by the selected tips is a mixture of Bernoulli sampled CPPs with the same parent CPP, over some explicit distribution of the sampling probability y. An immediate consequence is that the genealogy of a k-sample can be obtained by the realization of k random variables, first the random sampling probability Y and then the k−1 node depths which are iid conditional on Y=y.

Suggested Citation

  • Lambert, Amaury, 2018. "The coalescent of a sample from a binary branching process," Theoretical Population Biology, Elsevier, vol. 122(C), pages 30-35.
    • Handle: RePEc:eee:thpobi:v:122:y:2018:i:c:p:30-35
    DOI: 10.1016/j.tpb.2018.04.005
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    References listed on IDEAS

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    1. Lambert, Amaury & Stadler, Tanja, 2013. "Birth–death models and coalescent point processes: The shape and probability of reconstructed phylogenies," Theoretical Population Biology, Elsevier, vol. 90(C), pages 113-128.
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    Cited by:

    1. Ignatieva, Anastasia & Hein, Jotun & Jenkins, Paul A., 2020. "A characterisation of the reconstructed birth–death process through time rescaling," Theoretical Population Biology, Elsevier, vol. 134(C), pages 61-76.

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