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Ancestral reproductive bias in branching processes.
Cheek, David; Johnston, Samuel G G.
Afiliação
  • Cheek D; Massachusetts General Hospital and Harvard Medical School, 149 13th St., Charlestown, MA, 02129, USA.
  • Johnston SGG; Department of Mathematics, King's College London, Strand Building, London, WC2R 2LS, UK. samuel.g.johnston@kcl.ac.uk.
J Math Biol ; 86(5): 70, 2023 04 07.
Article em En | MEDLINE | ID: mdl-37027075
ABSTRACT
Consider a branching process whose reproduction law is homogeneous. Sampling a single cell uniformly from the population at a time [Formula see text] and looking along the sampled cell's ancestral lineage, we find that the reproduction law is heterogeneous-the expected reproductive output of ancestral cells on the lineage from time 0 to time T continuously increases with time. This 'inspection paradox' is due to sampling bias, that cells with a larger number of offspring are more likely to have one of their descendants sampled by virtue of their prolificity. The bias's strength changes with the random population size and/or the sampling time T. Our main result explicitly characterises the evolution of reproduction rates and sizes along the sampled ancestral lineage as a mixture of Poisson processes, which simplifies in special cases. The ancestral bias helps to explain recently observed variation in mutation rates along lineages of the developing human embryo.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Taxa de Mutação / Modelos Genéticos Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Taxa de Mutação / Modelos Genéticos Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article