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A continuous analog of run length distributions reflecting accumulated fractionation events

BACKGROUND: We propose a new, continuous model of the fractionation process (duplicate gene deletion after polyploidization) on the real line. The aim is to infer how much DNA is deleted at a time, based on segment lengths for alternating deleted (invisible) and undeleted (visible) regions. RESULTS:...

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Detalles Bibliográficos
Autores principales: Yu, Zhe, Sankoff, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5123346/
https://www.ncbi.nlm.nih.gov/pubmed/28185566
http://dx.doi.org/10.1186/s12859-016-1265-5
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author Yu, Zhe
Sankoff, David
author_facet Yu, Zhe
Sankoff, David
author_sort Yu, Zhe
collection PubMed
description BACKGROUND: We propose a new, continuous model of the fractionation process (duplicate gene deletion after polyploidization) on the real line. The aim is to infer how much DNA is deleted at a time, based on segment lengths for alternating deleted (invisible) and undeleted (visible) regions. RESULTS: After deriving a number of analytical results for “one-sided” fractionation, we undertake a series of simulations that help us identify the distribution of segment lengths as a gamma with shape and rate parameters evolving over time. This leads to an inference procedure based on observed length distributions for visible and invisible segments. CONCLUSIONS: We suggest extensions of this mathematical and simulation work to biologically realistic discrete models, including two-sided fractionation.
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spelling pubmed-51233462016-12-06 A continuous analog of run length distributions reflecting accumulated fractionation events Yu, Zhe Sankoff, David BMC Bioinformatics Research BACKGROUND: We propose a new, continuous model of the fractionation process (duplicate gene deletion after polyploidization) on the real line. The aim is to infer how much DNA is deleted at a time, based on segment lengths for alternating deleted (invisible) and undeleted (visible) regions. RESULTS: After deriving a number of analytical results for “one-sided” fractionation, we undertake a series of simulations that help us identify the distribution of segment lengths as a gamma with shape and rate parameters evolving over time. This leads to an inference procedure based on observed length distributions for visible and invisible segments. CONCLUSIONS: We suggest extensions of this mathematical and simulation work to biologically realistic discrete models, including two-sided fractionation. BioMed Central 2016-11-11 /pmc/articles/PMC5123346/ /pubmed/28185566 http://dx.doi.org/10.1186/s12859-016-1265-5 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Yu, Zhe
Sankoff, David
A continuous analog of run length distributions reflecting accumulated fractionation events
title A continuous analog of run length distributions reflecting accumulated fractionation events
title_full A continuous analog of run length distributions reflecting accumulated fractionation events
title_fullStr A continuous analog of run length distributions reflecting accumulated fractionation events
title_full_unstemmed A continuous analog of run length distributions reflecting accumulated fractionation events
title_short A continuous analog of run length distributions reflecting accumulated fractionation events
title_sort continuous analog of run length distributions reflecting accumulated fractionation events
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5123346/
https://www.ncbi.nlm.nih.gov/pubmed/28185566
http://dx.doi.org/10.1186/s12859-016-1265-5
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