Cargando…
A practical introduction to sequentially Markovian coalescent methods for estimating demographic history from genomic data
A common goal of population genomics and molecular ecology is to reconstruct the demographic history of a species of interest. A pair of powerful tools based on the sequentially Markovian coalescent have been developed to infer past population sizes using genome sequences. These methods are most use...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6972798/ https://www.ncbi.nlm.nih.gov/pubmed/31988743 http://dx.doi.org/10.1002/ece3.5888 |
_version_ | 1783489909147828224 |
---|---|
author | Mather, Niklas Traves, Samuel M. Ho, Simon Y. W. |
author_facet | Mather, Niklas Traves, Samuel M. Ho, Simon Y. W. |
author_sort | Mather, Niklas |
collection | PubMed |
description | A common goal of population genomics and molecular ecology is to reconstruct the demographic history of a species of interest. A pair of powerful tools based on the sequentially Markovian coalescent have been developed to infer past population sizes using genome sequences. These methods are most useful when sequences are available for only a limited number of genomes and when the aim is to study ancient demographic events. The results of these analyses can be difficult to interpret accurately, because doing so requires some understanding of their theoretical basis and of their sensitivity to confounding factors. In this practical review, we explain some of the key concepts underpinning the pairwise and multiple sequentially Markovian coalescent methods (PSMC and MSMC, respectively). We relate these concepts to the use and interpretation of these methods, and we explain how the choice of different parameter values by the user can affect the accuracy and precision of the inferences. Based on our survey of 100 PSMC studies and 30 MSMC studies, we describe how the two methods are used in practice. Readers of this article will become familiar with the principles, practice, and interpretation of the sequentially Markovian coalescent for inferring demographic history. |
format | Online Article Text |
id | pubmed-6972798 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-69727982020-01-27 A practical introduction to sequentially Markovian coalescent methods for estimating demographic history from genomic data Mather, Niklas Traves, Samuel M. Ho, Simon Y. W. Ecol Evol Review Article A common goal of population genomics and molecular ecology is to reconstruct the demographic history of a species of interest. A pair of powerful tools based on the sequentially Markovian coalescent have been developed to infer past population sizes using genome sequences. These methods are most useful when sequences are available for only a limited number of genomes and when the aim is to study ancient demographic events. The results of these analyses can be difficult to interpret accurately, because doing so requires some understanding of their theoretical basis and of their sensitivity to confounding factors. In this practical review, we explain some of the key concepts underpinning the pairwise and multiple sequentially Markovian coalescent methods (PSMC and MSMC, respectively). We relate these concepts to the use and interpretation of these methods, and we explain how the choice of different parameter values by the user can affect the accuracy and precision of the inferences. Based on our survey of 100 PSMC studies and 30 MSMC studies, we describe how the two methods are used in practice. Readers of this article will become familiar with the principles, practice, and interpretation of the sequentially Markovian coalescent for inferring demographic history. John Wiley and Sons Inc. 2019-12-07 /pmc/articles/PMC6972798/ /pubmed/31988743 http://dx.doi.org/10.1002/ece3.5888 Text en © 2019 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Mather, Niklas Traves, Samuel M. Ho, Simon Y. W. A practical introduction to sequentially Markovian coalescent methods for estimating demographic history from genomic data |
title | A practical introduction to sequentially Markovian coalescent methods for estimating demographic history from genomic data |
title_full | A practical introduction to sequentially Markovian coalescent methods for estimating demographic history from genomic data |
title_fullStr | A practical introduction to sequentially Markovian coalescent methods for estimating demographic history from genomic data |
title_full_unstemmed | A practical introduction to sequentially Markovian coalescent methods for estimating demographic history from genomic data |
title_short | A practical introduction to sequentially Markovian coalescent methods for estimating demographic history from genomic data |
title_sort | practical introduction to sequentially markovian coalescent methods for estimating demographic history from genomic data |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6972798/ https://www.ncbi.nlm.nih.gov/pubmed/31988743 http://dx.doi.org/10.1002/ece3.5888 |
work_keys_str_mv | AT matherniklas apracticalintroductiontosequentiallymarkoviancoalescentmethodsforestimatingdemographichistoryfromgenomicdata AT travessamuelm apracticalintroductiontosequentiallymarkoviancoalescentmethodsforestimatingdemographichistoryfromgenomicdata AT hosimonyw apracticalintroductiontosequentiallymarkoviancoalescentmethodsforestimatingdemographichistoryfromgenomicdata AT matherniklas practicalintroductiontosequentiallymarkoviancoalescentmethodsforestimatingdemographichistoryfromgenomicdata AT travessamuelm practicalintroductiontosequentiallymarkoviancoalescentmethodsforestimatingdemographichistoryfromgenomicdata AT hosimonyw practicalintroductiontosequentiallymarkoviancoalescentmethodsforestimatingdemographichistoryfromgenomicdata |