ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data

<p>Abstract</p> <p>Background</p> <p>With next-generation sequencing technologies, experiments that were considered prohibitive only a few years ago are now possible. However, while these technologies have the ability to produce enormous volumes of data, the sequence re...

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Main Authors: Eriksson Nicholas, Bhattacharya Arnab, Zagordi Osvaldo, Beerenwinkel Niko
Format: Article
Language:English
Published: BMC 2011-04-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/12/119
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author Eriksson Nicholas
Bhattacharya Arnab
Zagordi Osvaldo
Beerenwinkel Niko
author_facet Eriksson Nicholas
Bhattacharya Arnab
Zagordi Osvaldo
Beerenwinkel Niko
author_sort Eriksson Nicholas
collection DOAJ
description <p>Abstract</p> <p>Background</p> <p>With next-generation sequencing technologies, experiments that were considered prohibitive only a few years ago are now possible. However, while these technologies have the ability to produce enormous volumes of data, the sequence reads are prone to error. This poses fundamental hurdles when genetic diversity is investigated.</p> <p>Results</p> <p>We developed ShoRAH, a computational method for quantifying genetic diversity in a mixed sample and for identifying the individual clones in the population, while accounting for sequencing errors. The software was run on simulated data and on real data obtained in wet lab experiments to assess its reliability.</p> <p>Conclusions</p> <p>ShoRAH is implemented in C++, Python, and Perl and has been tested under Linux and Mac OS X. Source code is available under the GNU General Public License at <url>http://www.cbg.ethz.ch/software/shorah</url>.</p>
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spelling doaj.art-9420965b2c6a4ccc95204cd894b51f0f2022-12-21T23:26:48ZengBMCBMC Bioinformatics1471-21052011-04-0112111910.1186/1471-2105-12-119ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing dataEriksson NicholasBhattacharya ArnabZagordi OsvaldoBeerenwinkel Niko<p>Abstract</p> <p>Background</p> <p>With next-generation sequencing technologies, experiments that were considered prohibitive only a few years ago are now possible. However, while these technologies have the ability to produce enormous volumes of data, the sequence reads are prone to error. This poses fundamental hurdles when genetic diversity is investigated.</p> <p>Results</p> <p>We developed ShoRAH, a computational method for quantifying genetic diversity in a mixed sample and for identifying the individual clones in the population, while accounting for sequencing errors. The software was run on simulated data and on real data obtained in wet lab experiments to assess its reliability.</p> <p>Conclusions</p> <p>ShoRAH is implemented in C++, Python, and Perl and has been tested under Linux and Mac OS X. Source code is available under the GNU General Public License at <url>http://www.cbg.ethz.ch/software/shorah</url>.</p>http://www.biomedcentral.com/1471-2105/12/119
spellingShingle Eriksson Nicholas
Bhattacharya Arnab
Zagordi Osvaldo
Beerenwinkel Niko
ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data
BMC Bioinformatics
title ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data
title_full ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data
title_fullStr ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data
title_full_unstemmed ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data
title_short ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data
title_sort shorah estimating the genetic diversity of a mixed sample from next generation sequencing data
url http://www.biomedcentral.com/1471-2105/12/119
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