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The distribution of waiting distances in ancestral recombination graphs.
Deng, Yun; Song, Yun S; Nielsen, Rasmus.
Afiliación
  • Deng Y; Center for Computational Biology, University of California, Berkeley, CA 94720, United States of America. Electronic address: yun_deng@berkeley.edu.
  • Song YS; Department of Statistics, University of California, Berkeley, CA 94720, United States of America; Computer Science Division, University of California, Berkeley, CA 94720, United States of America; Chan Zuckerberg Biohub, San Francisco, CA 94158, United States of America.
  • Nielsen R; Department of Statistics, University of California, Berkeley, CA 94720, United States of America; Department of Integrative biology, University of California, Berkeley, CA 94720, United States of America. Electronic address: rasmus_nielsen@berkeley.edu.
Theor Popul Biol ; 141: 34-43, 2021 10.
Article en En | MEDLINE | ID: mdl-34186053
ABSTRACT
The ancestral recombination graph (ARG) contains the full genealogical information of the sample, and many population genetic inference problems can be solved using inferred or sampled ARGs. In particular, the waiting distance between tree changes along the genome can be used to make inference about the distribution and evolution of recombination rates. To this end, we here derive an analytic expression for the distribution of waiting distances between tree changes under the sequentially Markovian coalescent model and obtain an accurate approximation to the distribution of waiting distances for topology changes. We use these results to show that some of the recently proposed methods for inferring sequences of trees along the genome provide strongly biased distributions of waiting distances. In addition, we provide a correction to an undercounting problem facing all available ARG inference methods, thereby facilitating the use of ARG inference methods to estimate temporal changes in the recombination rate.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Recombinación Genética / Modelos Genéticos Tipo de estudio: Health_economic_evaluation Idioma: En Revista: Theor Popul Biol Año: 2021 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Recombinación Genética / Modelos Genéticos Tipo de estudio: Health_economic_evaluation Idioma: En Revista: Theor Popul Biol Año: 2021 Tipo del documento: Article