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

BMC Bioinformatics

Software

Nicholas Eriksson¹  Arnab Bhattacharya²  Osvaldo Zagordi³  Niko Beerenwinkel³ 

[1] 23andMe, 94043, Mountain View, CA, USA;Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058, Basel, Switzerland;Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058, Basel, Switzerland;SIB Swiss Institute of Bioinformatics, Switzerland;

关键词: Read Length;    Illumina Genome Analyzer;    Maximum Weight Match;    Local Haplotype;    Local Reconstruction;   

DOI  :  10.1186/1471-2105-12-119

 received in 2011-01-26, accepted in 2011-04-26,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundWith 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.ResultsWe 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.ConclusionsShoRAH 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 http://www.cbg.ethz.ch/software/shorah.

【 授权许可】

CC BY   
© Zagordi et al; licensee BioMed Central Ltd. 2011