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

Reinert, Knut; Dadi, Temesgen Hailemariam; Ehrhardt, Marcel; Hauswedell , Hannes; Mehringer, Svenja; Rahn, René; Kim, Jongkyu; Pockrandt, Christopher; Winkler, Jörg; Siragusa, Enrico; Urgese, Gianvito; Weese, David

doi:10.1016/j.jbiotec.2017.07.017

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

MPS-Authors

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Reinert, Knut
Efficient Algorithms for Omics Data (Knut Reinert), Max Planck Fellow Group, Max Planck Institute for Molecular Genetics, Max Planck Society;

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Dadi, Temesgen Hailemariam
IMPRS for Biology and Computation (Anne-Dominique Gindrat), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Mehringer, Svenja
IMPRS for Biology and Computation (Anne-Dominique Gindrat), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

Kim, Jongkyu
IMPRS for Biology and Computation (Anne-Dominique Gindrat), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

Pockrandt, Christopher
IMPRS for Biology and Computation (Anne-Dominique Gindrat), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

Winkler, Jörg
IMPRS for Biology and Computation (Anne-Dominique Gindrat), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Journal Biotechnol_Reinert et al_2017.pdf
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引用

Reinert, K., Dadi, T. H., Ehrhardt, M., Hauswedell, H., Mehringer, S., Rahn, R., Kim, J., Pockrandt, C., Winkler, J., Siragusa, E., Urgese, G., & Weese, D. (2017). The SeqAn C++ template library for efficient sequence analysis: A resource for programmers. Journal of Biotechnology, 261, 157-168. doi:10.1016/j.jbiotec.2017.07.017.

引用: https://hdl.handle.net/21.11116/0000-000E-5ABE-8

要旨

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.