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SNeP: a tool to estimate trends in recent effective population size trajectories using genome-wide SNP data
Effective population size (N(e)) is a key population genetic parameter that describes the amount of genetic drift in a population. Estimating N(e) has been subject to much research over the last 80 years. Methods to estimate N(e) from linkage disequilibrium (LD) were developed ~40 years ago but depe...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4367434/ https://www.ncbi.nlm.nih.gov/pubmed/25852748 http://dx.doi.org/10.3389/fgene.2015.00109 |
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author | Barbato, Mario Orozco-terWengel, Pablo Tapio, Miika Bruford, Michael W. |
author_facet | Barbato, Mario Orozco-terWengel, Pablo Tapio, Miika Bruford, Michael W. |
author_sort | Barbato, Mario |
collection | PubMed |
description | Effective population size (N(e)) is a key population genetic parameter that describes the amount of genetic drift in a population. Estimating N(e) has been subject to much research over the last 80 years. Methods to estimate N(e) from linkage disequilibrium (LD) were developed ~40 years ago but depend on the availability of large amounts of genetic marker data that only the most recent advances in DNA technology have made available. Here we introduce SNeP, a multithreaded tool to perform the estimate of N(e) using LD using the standard PLINK input file format (.ped and.map files) or by using LD values calculated using other software. Through SNeP the user can apply several corrections to take account of sample size, mutation, phasing, and recombination rate. Each variable involved in the computation such as the binning parameters or the chromosomes to include in the analysis can be modified. When applied to published datasets, SNeP produced results closely comparable with those obtained in the original studies. The use of SNeP to estimate N(e) trends can improve understanding of population demography in the recent past, provided a sufficient number of SNPs and their physical position in the genome are available. Binaries for the most common operating systems are available at https://sourceforge.net/projects/snepnetrends/. |
format | Online Article Text |
id | pubmed-4367434 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-43674342015-04-07 SNeP: a tool to estimate trends in recent effective population size trajectories using genome-wide SNP data Barbato, Mario Orozco-terWengel, Pablo Tapio, Miika Bruford, Michael W. Front Genet Genetics Effective population size (N(e)) is a key population genetic parameter that describes the amount of genetic drift in a population. Estimating N(e) has been subject to much research over the last 80 years. Methods to estimate N(e) from linkage disequilibrium (LD) were developed ~40 years ago but depend on the availability of large amounts of genetic marker data that only the most recent advances in DNA technology have made available. Here we introduce SNeP, a multithreaded tool to perform the estimate of N(e) using LD using the standard PLINK input file format (.ped and.map files) or by using LD values calculated using other software. Through SNeP the user can apply several corrections to take account of sample size, mutation, phasing, and recombination rate. Each variable involved in the computation such as the binning parameters or the chromosomes to include in the analysis can be modified. When applied to published datasets, SNeP produced results closely comparable with those obtained in the original studies. The use of SNeP to estimate N(e) trends can improve understanding of population demography in the recent past, provided a sufficient number of SNPs and their physical position in the genome are available. Binaries for the most common operating systems are available at https://sourceforge.net/projects/snepnetrends/. Frontiers Media S.A. 2015-03-20 /pmc/articles/PMC4367434/ /pubmed/25852748 http://dx.doi.org/10.3389/fgene.2015.00109 Text en Copyright © 2015 Barbato, Orozco-terWengel, Tapio and Bruford. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Barbato, Mario Orozco-terWengel, Pablo Tapio, Miika Bruford, Michael W. SNeP: a tool to estimate trends in recent effective population size trajectories using genome-wide SNP data |
title | SNeP: a tool to estimate trends in recent effective population size trajectories using genome-wide SNP data |
title_full | SNeP: a tool to estimate trends in recent effective population size trajectories using genome-wide SNP data |
title_fullStr | SNeP: a tool to estimate trends in recent effective population size trajectories using genome-wide SNP data |
title_full_unstemmed | SNeP: a tool to estimate trends in recent effective population size trajectories using genome-wide SNP data |
title_short | SNeP: a tool to estimate trends in recent effective population size trajectories using genome-wide SNP data |
title_sort | snep: a tool to estimate trends in recent effective population size trajectories using genome-wide snp data |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4367434/ https://www.ncbi.nlm.nih.gov/pubmed/25852748 http://dx.doi.org/10.3389/fgene.2015.00109 |
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