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

• Published in: BMC bioinformatics Vol. 12; no. 1; p. 119
• Main Authors: Zagordi, Osvaldo, Bhattacharya, Arnab, Eriksson, Nicholas, Beerenwinkel, Niko
• Format: Journal Article
• Language: English
• Published: London BioMed Central 26.04.2011; BioMed Central Ltd; BMC
• Subjects: Algorithms; Bioinformatics; Biological diversity; Biomedical and Life Sciences; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Computer applications; Computer programs; Data processing; Genetic aspects; Genetic diversity; Genetic Variation; High-Throughput Nucleotide Sequencing - economics; High-Throughput Nucleotide Sequencing - methods; HIV - genetics; HIV Infections - virology; Humans; Life Sciences; Microarrays; Neoplasms - genetics; Public software; Sequence analysis (applications); Sequence Analysis, DNA - economics; Sequence Analysis, DNA - methods; Software; United States; Switzerland; Read Length; Local Haplotype; Illumina Genome Analyzer; Local Reconstruction; Maximum Weight Match
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/1471-2105-12-119

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 .