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Detecting individual ancestry in the human genome
Detecting and quantifying the population substructure present in a sample of individuals are of main interest in the fields of genetic epidemiology, population genetics, and forensics among others. To date, several algorithms have been proposed for estimating the amount of genetic ancestry within an...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4416275/ https://www.ncbi.nlm.nih.gov/pubmed/25937887 http://dx.doi.org/10.1186/s13323-015-0019-x |
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author | Wollstein, Andreas Lao, Oscar |
author_facet | Wollstein, Andreas Lao, Oscar |
author_sort | Wollstein, Andreas |
collection | PubMed |
description | Detecting and quantifying the population substructure present in a sample of individuals are of main interest in the fields of genetic epidemiology, population genetics, and forensics among others. To date, several algorithms have been proposed for estimating the amount of genetic ancestry within an individual. In the present review, we introduce the most widely used methods in population genetics for detecting individual genetic ancestry. We further show, by means of simulations, the performance of popular algorithms for detecting individual ancestry in various controlled demographic scenarios. Finally, we provide some hints on how to interpret the results from these algorithms. |
format | Online Article Text |
id | pubmed-4416275 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-44162752015-05-02 Detecting individual ancestry in the human genome Wollstein, Andreas Lao, Oscar Investig Genet Review Detecting and quantifying the population substructure present in a sample of individuals are of main interest in the fields of genetic epidemiology, population genetics, and forensics among others. To date, several algorithms have been proposed for estimating the amount of genetic ancestry within an individual. In the present review, we introduce the most widely used methods in population genetics for detecting individual genetic ancestry. We further show, by means of simulations, the performance of popular algorithms for detecting individual ancestry in various controlled demographic scenarios. Finally, we provide some hints on how to interpret the results from these algorithms. BioMed Central 2015-05-01 /pmc/articles/PMC4416275/ /pubmed/25937887 http://dx.doi.org/10.1186/s13323-015-0019-x Text en © Wollstein and Lao; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 | Review Wollstein, Andreas Lao, Oscar Detecting individual ancestry in the human genome |
title | Detecting individual ancestry in the human genome |
title_full | Detecting individual ancestry in the human genome |
title_fullStr | Detecting individual ancestry in the human genome |
title_full_unstemmed | Detecting individual ancestry in the human genome |
title_short | Detecting individual ancestry in the human genome |
title_sort | detecting individual ancestry in the human genome |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4416275/ https://www.ncbi.nlm.nih.gov/pubmed/25937887 http://dx.doi.org/10.1186/s13323-015-0019-x |
work_keys_str_mv | AT wollsteinandreas detectingindividualancestryinthehumangenome AT laooscar detectingindividualancestryinthehumangenome |