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4P: fast computing of population genetics statistics from large DNA polymorphism panels
Massive DNA sequencing has significantly increased the amount of data available for population genetics and molecular ecology studies. However, the parallel computation of simple statistics within and between populations from large panels of polymorphic sites is not yet available, making the explora...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BlackWell Publishing Ltd
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4298444/ https://www.ncbi.nlm.nih.gov/pubmed/25628874 http://dx.doi.org/10.1002/ece3.1261 |
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author | Benazzo, Andrea Panziera, Alex Bertorelle, Giorgio |
author_facet | Benazzo, Andrea Panziera, Alex Bertorelle, Giorgio |
author_sort | Benazzo, Andrea |
collection | PubMed |
description | Massive DNA sequencing has significantly increased the amount of data available for population genetics and molecular ecology studies. However, the parallel computation of simple statistics within and between populations from large panels of polymorphic sites is not yet available, making the exploratory analyses of a set or subset of data a very laborious task. Here, we present 4P (parallel processing of polymorphism panels), a stand-alone software program for the rapid computation of genetic variation statistics (including the joint frequency spectrum) from millions of DNA variants in multiple individuals and multiple populations. It handles a standard input file format commonly used to store DNA variation from empirical or simulation experiments. The computational performance of 4P was evaluated using large SNP (single nucleotide polymorphism) datasets from human genomes or obtained by simulations. 4P was faster or much faster than other comparable programs, and the impact of parallel computing using multicore computers or servers was evident. 4P is a useful tool for biologists who need a simple and rapid computer program to run exploratory population genetics analyses in large panels of genomic data. It is also particularly suitable to analyze multiple data sets produced in simulation studies. Unix, Windows, and MacOs versions are provided, as well as the source code for easier pipeline implementations. |
format | Online Article Text |
id | pubmed-4298444 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BlackWell Publishing Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-42984442015-01-27 4P: fast computing of population genetics statistics from large DNA polymorphism panels Benazzo, Andrea Panziera, Alex Bertorelle, Giorgio Ecol Evol Original Research Massive DNA sequencing has significantly increased the amount of data available for population genetics and molecular ecology studies. However, the parallel computation of simple statistics within and between populations from large panels of polymorphic sites is not yet available, making the exploratory analyses of a set or subset of data a very laborious task. Here, we present 4P (parallel processing of polymorphism panels), a stand-alone software program for the rapid computation of genetic variation statistics (including the joint frequency spectrum) from millions of DNA variants in multiple individuals and multiple populations. It handles a standard input file format commonly used to store DNA variation from empirical or simulation experiments. The computational performance of 4P was evaluated using large SNP (single nucleotide polymorphism) datasets from human genomes or obtained by simulations. 4P was faster or much faster than other comparable programs, and the impact of parallel computing using multicore computers or servers was evident. 4P is a useful tool for biologists who need a simple and rapid computer program to run exploratory population genetics analyses in large panels of genomic data. It is also particularly suitable to analyze multiple data sets produced in simulation studies. Unix, Windows, and MacOs versions are provided, as well as the source code for easier pipeline implementations. BlackWell Publishing Ltd 2015-01 2014-12-11 /pmc/articles/PMC4298444/ /pubmed/25628874 http://dx.doi.org/10.1002/ece3.1261 Text en © 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. http://creativecommons.org/licenses/by/3.0/ This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Research Benazzo, Andrea Panziera, Alex Bertorelle, Giorgio 4P: fast computing of population genetics statistics from large DNA polymorphism panels |
title | 4P: fast computing of population genetics statistics from large DNA polymorphism panels |
title_full | 4P: fast computing of population genetics statistics from large DNA polymorphism panels |
title_fullStr | 4P: fast computing of population genetics statistics from large DNA polymorphism panels |
title_full_unstemmed | 4P: fast computing of population genetics statistics from large DNA polymorphism panels |
title_short | 4P: fast computing of population genetics statistics from large DNA polymorphism panels |
title_sort | 4p: fast computing of population genetics statistics from large dna polymorphism panels |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4298444/ https://www.ncbi.nlm.nih.gov/pubmed/25628874 http://dx.doi.org/10.1002/ece3.1261 |
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