title: ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data.
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.
authors.affiliation: Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland. osvaldo.zagordi@bsse.ethz.ch
authors.forename: Osvaldo
authors.initials: O
authors.lastname: Zagordi
authors.forename: Arnab
authors.initials: A
authors.lastname: Bhattacharya
authors.forename: Nicholas
authors.initials: N
authors.lastname: Eriksson
authors.forename: Niko
authors.initials: N
authors.lastname: Beerenwinkel
mesh_terms: D014644:Genetic Variation; D006678:HIV / Q000235:genetics; D015658:HIV Infections / Q000821:virology; D059014:High-Throughput Nucleotide Sequencing / Q000191:economics / Q000379:methods*; D006801:Humans; D009369:Neoplasms / Q000235:genetics; D017422:Sequence Analysis, DNA / Q000191:economics / Q000379:methods*; D012984:Software