ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data
Open access
Date
2011-04Type
- Journal Article
ETH Bibliography
yes
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Abstract
Background
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.
Results
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.
Conclusions
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 http://www.cbg.ethz.ch/software/shorah. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000037475Publication status
publishedExternal links
Journal / series
BMC BioinformaticsVolume
Pages / Article No.
Publisher
BioMed CentralSubject
Read Length; Illumina Genome Analyzer; Maximum Weight Match; Local Haplotype; Local ReconstructionOrganisational unit
03790 - Beerenwinkel, Niko / Beerenwinkel, Niko
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ETH Bibliography
yes
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