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nQuire: a statistical framework for ploidy estimation using next generation sequencing
BACKGROUND: Intraspecific variation in ploidy occurs in a wide range of species including pathogenic and nonpathogenic eukaryotes such as yeasts and oomycetes. Ploidy can be inferred indirectly - without measuring DNA content - from experiments using next-generation sequencing (NGS). We present nQui...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5885312/ https://www.ncbi.nlm.nih.gov/pubmed/29618319 http://dx.doi.org/10.1186/s12859-018-2128-z |
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author | Weiß, Clemens L. Pais, Marina Cano, Liliana M. Kamoun, Sophien Burbano, Hernán A. |
author_facet | Weiß, Clemens L. Pais, Marina Cano, Liliana M. Kamoun, Sophien Burbano, Hernán A. |
author_sort | Weiß, Clemens L. |
collection | PubMed |
description | BACKGROUND: Intraspecific variation in ploidy occurs in a wide range of species including pathogenic and nonpathogenic eukaryotes such as yeasts and oomycetes. Ploidy can be inferred indirectly - without measuring DNA content - from experiments using next-generation sequencing (NGS). We present nQuire, a statistical framework that distinguishes between diploids, triploids and tetraploids using NGS. The command-line tool models the distribution of base frequencies at variable sites using a Gaussian Mixture Model, and uses maximum likelihood to select the most plausible ploidy model. nQuire handles large genomes at high coverage efficiently and uses standard input file formats. RESULTS: We demonstrate the utility of nQuire analyzing individual samples of the pathogenic oomycete Phytophthora infestans and the Baker’s yeast Saccharomyces cerevisiae. Using these organisms we show the dependence between reliability of the ploidy assignment and sequencing depth. Additionally, we employ normalized maximized log- likelihoods generated by nQuire to ascertain ploidy level in a population of samples with ploidy heterogeneity. Using these normalized values we cluster samples in three dimensions using multivariate Gaussian mixtures. The cluster assignments retrieved from a S. cerevisiae population recovered the true ploidy level in over 96% of samples. Finally, we show that nQuire can be used regionally to identify chromosomal aneuploidies. CONCLUSIONS: nQuire provides a statistical framework to study organisms with intraspecific variation in ploidy. nQuire is likely to be useful in epidemiological studies of pathogens, artificial selection experiments, and for historical or ancient samples where intact nuclei are not preserved. It is implemented as a stand-alone Linux command line tool in the C programming language and is available at https://github.com/clwgg/nQuireunder the MIT license. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2128-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5885312 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-58853122018-04-09 nQuire: a statistical framework for ploidy estimation using next generation sequencing Weiß, Clemens L. Pais, Marina Cano, Liliana M. Kamoun, Sophien Burbano, Hernán A. BMC Bioinformatics Methodology Article BACKGROUND: Intraspecific variation in ploidy occurs in a wide range of species including pathogenic and nonpathogenic eukaryotes such as yeasts and oomycetes. Ploidy can be inferred indirectly - without measuring DNA content - from experiments using next-generation sequencing (NGS). We present nQuire, a statistical framework that distinguishes between diploids, triploids and tetraploids using NGS. The command-line tool models the distribution of base frequencies at variable sites using a Gaussian Mixture Model, and uses maximum likelihood to select the most plausible ploidy model. nQuire handles large genomes at high coverage efficiently and uses standard input file formats. RESULTS: We demonstrate the utility of nQuire analyzing individual samples of the pathogenic oomycete Phytophthora infestans and the Baker’s yeast Saccharomyces cerevisiae. Using these organisms we show the dependence between reliability of the ploidy assignment and sequencing depth. Additionally, we employ normalized maximized log- likelihoods generated by nQuire to ascertain ploidy level in a population of samples with ploidy heterogeneity. Using these normalized values we cluster samples in three dimensions using multivariate Gaussian mixtures. The cluster assignments retrieved from a S. cerevisiae population recovered the true ploidy level in over 96% of samples. Finally, we show that nQuire can be used regionally to identify chromosomal aneuploidies. CONCLUSIONS: nQuire provides a statistical framework to study organisms with intraspecific variation in ploidy. nQuire is likely to be useful in epidemiological studies of pathogens, artificial selection experiments, and for historical or ancient samples where intact nuclei are not preserved. It is implemented as a stand-alone Linux command line tool in the C programming language and is available at https://github.com/clwgg/nQuireunder the MIT license. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2128-z) contains supplementary material, which is available to authorized users. BioMed Central 2018-04-04 /pmc/articles/PMC5885312/ /pubmed/29618319 http://dx.doi.org/10.1186/s12859-018-2128-z Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 | Methodology Article Weiß, Clemens L. Pais, Marina Cano, Liliana M. Kamoun, Sophien Burbano, Hernán A. nQuire: a statistical framework for ploidy estimation using next generation sequencing |
title | nQuire: a statistical framework for ploidy estimation using next generation sequencing |
title_full | nQuire: a statistical framework for ploidy estimation using next generation sequencing |
title_fullStr | nQuire: a statistical framework for ploidy estimation using next generation sequencing |
title_full_unstemmed | nQuire: a statistical framework for ploidy estimation using next generation sequencing |
title_short | nQuire: a statistical framework for ploidy estimation using next generation sequencing |
title_sort | nquire: a statistical framework for ploidy estimation using next generation sequencing |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5885312/ https://www.ncbi.nlm.nih.gov/pubmed/29618319 http://dx.doi.org/10.1186/s12859-018-2128-z |
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