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Fast half-sibling population reconstruction: theory and algorithms
BACKGROUND: Kinship inference is the task of identifying genealogically related individuals. Kinship information is important for determining mating structures, notably in endangered populations. Although many solutions exist for reconstructing full sibling relationships, few exist for half-siblings...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3738158/ https://www.ncbi.nlm.nih.gov/pubmed/23849037 http://dx.doi.org/10.1186/1748-7188-8-20 |
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author | Dexter, Daniel Brown, Daniel G |
author_facet | Dexter, Daniel Brown, Daniel G |
author_sort | Dexter, Daniel |
collection | PubMed |
description | BACKGROUND: Kinship inference is the task of identifying genealogically related individuals. Kinship information is important for determining mating structures, notably in endangered populations. Although many solutions exist for reconstructing full sibling relationships, few exist for half-siblings. RESULTS: We consider the problem of determining whether a proposed half-sibling population reconstruction is valid under Mendelian inheritance assumptions. We show that this problem is NP-complete and provide a 0/1 integer program that identifies the minimum number of individuals that must be removed from a population in order for the reconstruction to become valid. We also present SibJoin, a heuristic-based clustering approach based on Mendelian genetics, which is strikingly fast. The software is available at http://github.com/ddexter/SibJoin.git+. CONCLUSIONS: Our SibJoin algorithm is reasonably accurate and thousands of times faster than existing algorithms. The heuristic is used to infer a half-sibling structure for a population which was, until recently, too large to evaluate. |
format | Online Article Text |
id | pubmed-3738158 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-37381582013-08-09 Fast half-sibling population reconstruction: theory and algorithms Dexter, Daniel Brown, Daniel G Algorithms Mol Biol Research BACKGROUND: Kinship inference is the task of identifying genealogically related individuals. Kinship information is important for determining mating structures, notably in endangered populations. Although many solutions exist for reconstructing full sibling relationships, few exist for half-siblings. RESULTS: We consider the problem of determining whether a proposed half-sibling population reconstruction is valid under Mendelian inheritance assumptions. We show that this problem is NP-complete and provide a 0/1 integer program that identifies the minimum number of individuals that must be removed from a population in order for the reconstruction to become valid. We also present SibJoin, a heuristic-based clustering approach based on Mendelian genetics, which is strikingly fast. The software is available at http://github.com/ddexter/SibJoin.git+. CONCLUSIONS: Our SibJoin algorithm is reasonably accurate and thousands of times faster than existing algorithms. The heuristic is used to infer a half-sibling structure for a population which was, until recently, too large to evaluate. BioMed Central 2013-07-12 /pmc/articles/PMC3738158/ /pubmed/23849037 http://dx.doi.org/10.1186/1748-7188-8-20 Text en Copyright © 2013 Dexter and Brown; 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 | Research Dexter, Daniel Brown, Daniel G Fast half-sibling population reconstruction: theory and algorithms |
title | Fast half-sibling population reconstruction: theory and algorithms |
title_full | Fast half-sibling population reconstruction: theory and algorithms |
title_fullStr | Fast half-sibling population reconstruction: theory and algorithms |
title_full_unstemmed | Fast half-sibling population reconstruction: theory and algorithms |
title_short | Fast half-sibling population reconstruction: theory and algorithms |
title_sort | fast half-sibling population reconstruction: theory and algorithms |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3738158/ https://www.ncbi.nlm.nih.gov/pubmed/23849037 http://dx.doi.org/10.1186/1748-7188-8-20 |
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