ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data
1 Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland
2 SIB Swiss Institute of Bioinformatics, Switzerland
3 23andMe, Mountain View, CA 94043, USA
BMC Bioinformatics 2011, 12:119 doi:10.1186/1471-2105-12-119Published: 26 April 2011
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.
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.
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 webcite.