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DivStat: A User-Friendly Tool for Single Nucleotide Polymorphism Analysis of Genomic Diversity

Recent developments have led to an enormous increase of publicly available large genomic data, including complete genomes. The 1000 Genomes Project was a major contributor, releasing the results of sequencing a large number of individual genomes, and allowing for a myriad of large scale studies on h...

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Detalles Bibliográficos
Autores principales: Soares, Inês, Moleirinho, Ana, Oliveira, Gonçalo N. P., Amorim, António
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4355611/
https://www.ncbi.nlm.nih.gov/pubmed/25756185
http://dx.doi.org/10.1371/journal.pone.0119851
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author Soares, Inês
Moleirinho, Ana
Oliveira, Gonçalo N. P.
Amorim, António
author_facet Soares, Inês
Moleirinho, Ana
Oliveira, Gonçalo N. P.
Amorim, António
author_sort Soares, Inês
collection PubMed
description Recent developments have led to an enormous increase of publicly available large genomic data, including complete genomes. The 1000 Genomes Project was a major contributor, releasing the results of sequencing a large number of individual genomes, and allowing for a myriad of large scale studies on human genetic variation. However, the tools currently available are insufficient when the goal concerns some analyses of data sets encompassing more than hundreds of base pairs and when considering haplotype sequences of single nucleotide polymorphisms (SNPs). Here, we present a new and potent tool to deal with large data sets allowing the computation of a variety of summary statistics of population genetic data, increasing the speed of data analysis.
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spelling pubmed-43556112015-03-17 DivStat: A User-Friendly Tool for Single Nucleotide Polymorphism Analysis of Genomic Diversity Soares, Inês Moleirinho, Ana Oliveira, Gonçalo N. P. Amorim, António PLoS One Research Article Recent developments have led to an enormous increase of publicly available large genomic data, including complete genomes. The 1000 Genomes Project was a major contributor, releasing the results of sequencing a large number of individual genomes, and allowing for a myriad of large scale studies on human genetic variation. However, the tools currently available are insufficient when the goal concerns some analyses of data sets encompassing more than hundreds of base pairs and when considering haplotype sequences of single nucleotide polymorphisms (SNPs). Here, we present a new and potent tool to deal with large data sets allowing the computation of a variety of summary statistics of population genetic data, increasing the speed of data analysis. Public Library of Science 2015-03-10 /pmc/articles/PMC4355611/ /pubmed/25756185 http://dx.doi.org/10.1371/journal.pone.0119851 Text en © 2015 Soares et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Soares, Inês
Moleirinho, Ana
Oliveira, Gonçalo N. P.
Amorim, António
DivStat: A User-Friendly Tool for Single Nucleotide Polymorphism Analysis of Genomic Diversity
title DivStat: A User-Friendly Tool for Single Nucleotide Polymorphism Analysis of Genomic Diversity
title_full DivStat: A User-Friendly Tool for Single Nucleotide Polymorphism Analysis of Genomic Diversity
title_fullStr DivStat: A User-Friendly Tool for Single Nucleotide Polymorphism Analysis of Genomic Diversity
title_full_unstemmed DivStat: A User-Friendly Tool for Single Nucleotide Polymorphism Analysis of Genomic Diversity
title_short DivStat: A User-Friendly Tool for Single Nucleotide Polymorphism Analysis of Genomic Diversity
title_sort divstat: a user-friendly tool for single nucleotide polymorphism analysis of genomic diversity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4355611/
https://www.ncbi.nlm.nih.gov/pubmed/25756185
http://dx.doi.org/10.1371/journal.pone.0119851
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