Algorithmic Bioinformatics, Institute for Bioinformatics, FU Berlin, Takustrasse 9, 14195 Berlin, Germany.
Algorithmic Bioinformatics, Institute for Bioinformatics, FU Berlin, Takustrasse 9, 14195 Berlin, Germany.
J Biotechnol. 2017 Nov 10;261:157-168. doi: 10.1016/j.jbiotec.2017.07.017. Epub 2017 Sep 6.
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).
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.
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.
新型算法技术对于生命科学中的许多重要问题至关重要。例如,如果没有先进的组装算法,人类基因组的测序(Venter 等人,2001)是不可能实现的,而实用的基于 BWT 的读映射器的发展对于 NGS 分析也非常重要。然而,由于技术进步的速度非常快,并且对生物信息学工具的需求迫切,最先进的算法技术与广泛使用的工具的实际算法组件之间存在越来越大的差距。我们之前通过在 2008 年引入高效数据类型和算法的 SeqAn 库(Döring 等人,2008)来解决这个问题。
自 9 年前首次发布以来,SeqAn 库已经成熟了很多。在本文中,我们回顾了它作为序列分析领域程序员的既定资源的地位,以及它对许多分析工具的贡献。
我们预计 SeqAn 将继续成为一个有价值的资源,特别是因为它开始以系统的方式积极支持各种硬件加速技术。