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Updated: Jun 2, 2026

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons
Published on: August 29, 2014
ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data
Osvaldo Zagordi1, Arnab Bhattacharya, Nicholas Eriksson
1Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland. osvaldo.zagordi@bsse.ethz.ch
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.
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