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Fast "coalescent" simulation

BACKGROUND: The amount of genome-wide molecular data is increasing rapidly, as is interest in developing methods appropriate for such data. There is a consequent increasing need for methods that are able to efficiently simulate such data. In this paper we implement the sequentially Markovian coalesc...

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Detalles Bibliográficos
Autores principales: Marjoram, Paul, Wall, Jeff D
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1458357/
https://www.ncbi.nlm.nih.gov/pubmed/16539698
http://dx.doi.org/10.1186/1471-2156-7-16
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author Marjoram, Paul
Wall, Jeff D
author_facet Marjoram, Paul
Wall, Jeff D
author_sort Marjoram, Paul
collection PubMed
description BACKGROUND: The amount of genome-wide molecular data is increasing rapidly, as is interest in developing methods appropriate for such data. There is a consequent increasing need for methods that are able to efficiently simulate such data. In this paper we implement the sequentially Markovian coalescent algorithm described by McVean and Cardin and present a further modification to that algorithm which slightly improves the closeness of the approximation to the full coalescent model. The algorithm ignores a class of recombination events known to affect the behavior of the genealogy of the sample, but which do not appear to affect the behavior of generated samples to any substantial degree. RESULTS: We show that our software is able to simulate large chromosomal regions, such as those appropriate in a consideration of genome-wide data, in a way that is several orders of magnitude faster than existing coalescent algorithms. CONCLUSION: This algorithm provides a useful resource for those needing to simulate large quantities of data for chromosomal-length regions using an approach that is much more efficient than traditional coalescent models.
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spelling pubmed-14583572006-05-08 Fast "coalescent" simulation Marjoram, Paul Wall, Jeff D BMC Genet Software BACKGROUND: The amount of genome-wide molecular data is increasing rapidly, as is interest in developing methods appropriate for such data. There is a consequent increasing need for methods that are able to efficiently simulate such data. In this paper we implement the sequentially Markovian coalescent algorithm described by McVean and Cardin and present a further modification to that algorithm which slightly improves the closeness of the approximation to the full coalescent model. The algorithm ignores a class of recombination events known to affect the behavior of the genealogy of the sample, but which do not appear to affect the behavior of generated samples to any substantial degree. RESULTS: We show that our software is able to simulate large chromosomal regions, such as those appropriate in a consideration of genome-wide data, in a way that is several orders of magnitude faster than existing coalescent algorithms. CONCLUSION: This algorithm provides a useful resource for those needing to simulate large quantities of data for chromosomal-length regions using an approach that is much more efficient than traditional coalescent models. BioMed Central 2006-03-15 /pmc/articles/PMC1458357/ /pubmed/16539698 http://dx.doi.org/10.1186/1471-2156-7-16 Text en Copyright © 2006 Marjoram and Wall; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Marjoram, Paul
Wall, Jeff D
Fast "coalescent" simulation
title Fast "coalescent" simulation
title_full Fast "coalescent" simulation
title_fullStr Fast "coalescent" simulation
title_full_unstemmed Fast "coalescent" simulation
title_short Fast "coalescent" simulation
title_sort fast "coalescent" simulation
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1458357/
https://www.ncbi.nlm.nih.gov/pubmed/16539698
http://dx.doi.org/10.1186/1471-2156-7-16
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