Repository: Freie Universität Berlin, Math Department

The SeqAn C++ template library for efficient sequence analysis: A resource for programmers

Reinert, Knut and Dadi, Temesgen Hailemariam and Ehrhardt, Marcel and Hauswedell, Hannes and Mehringer, Svenja and Rahn, René and Kim, Jongkyu and Pockrandt, Christopher and Winkler, Jörg and Siragusa, Enrico and Urgese, Gianvito and Weese, David (2017) The SeqAn C++ template library for efficient sequence analysis: A resource for programmers. Journal of Biotechnology, 261 . pp. 157-168. ISSN 01681656

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Official URL: http://doi.org/10.1016/j.jbiotec.2017.07.017

Abstract

Background The use of novel algorithmic techniques is pivotal to many important problems in life science. For example the sequencing of the human genome (Venter et al., 2001) would not have been possible without advanced assembly algorithms and the development of practical BWT based read mappers have been instrumental for NGS analysis. However, owing to the high speed of technological progress and the urgent need for bioinformatics tools, there was a widening gap between state-of-the-art algorithmic techniques and the actual algorithmic components of tools that are in widespread use. We previously addressed this by introducing the SeqAn library of efficient data types and algorithms in 2008 (Döring et al., 2008). Results The SeqAn library has matured considerably since its first publication 9 years ago. In this article we review its status as an established resource for programmers in the field of sequence analysis and its contributions to many analysis tools. Conclusions We anticipate that SeqAn will continue to be a valuable resource, especially since it started to actively support various hardware acceleration techniques in a systematic manner. Keywords NGS analysis; Software libraries; C++; Data structures

Item Type:Article
Uncontrolled Keywords:NGS analysis; Software libraries; C++; Data structures
Subjects:Mathematical and Computer Sciences > Computer Science
Divisions:Department of Mathematics and Computer Science > Institute of Computer Science > Algorithmic Bioinformatics Group
ID Code:2103
Deposited By: Anja Kasseckert
Deposited On:12 Sep 2017 14:16
Last Modified:12 Oct 2017 11:37

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