FAMSA: Fast and accurate multiple sequence alignment of huge protein families.
FAMSA: Fast and accurate multiple sequence alignment of huge protein families.
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DOI：
10.1038/srep33964
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发表时间：
2016-09-27
影响因子：
4.6
通讯作者：
Gudyś A
中科院分区：
文献类型：
--
作者：
Deorowicz S;Debudaj-Grabysz A;Gudyś A
现代测序平台的快速发展促进了蛋白质家族数据库的空前增长。包含数十万个序列的丰富集合对于多序列比对算法是一个巨大的挑战。本文介绍了FAMSA，一种新的渐进式算法，旨在快速，准确地比对数以千计的蛋白质序列。它的特点包括利用最长的共同子序列的措施，以确定成对的相似性，一种新的方法来评估差距成本，和一个新的迭代细化计划。重要的是，它的实现是高度优化和并行化的，以充分利用现代计算机平台。由于上述原因，质量指标（即对和和总列得分）表明FAMSA优于竞争算法，例如用于超过几千个序列的数据集的Clustal Omega或MAFFT，这些算法具有上级性能。质量不会影响时间或内存要求，这些要求比现有解决方案低一个数量级。例如，在不到两个小时的时间内分析了一系列415519个序列，并且需要不超过8 GB的RAM。FAMSA可在http://sun.aei.polsl.pl/REFRESH/famsa免费获得。
Rapid development of modern sequencing platforms has contributed to the unprecedented growth of protein families databases. The abundance of sets containing hundreds of thousands of sequences is a formidable challenge for multiple sequence alignment algorithms. The article introduces FAMSA, a new progressive algorithm designed for fast and accurate alignment of thousands of protein sequences. Its features include the utilization of the longest common subsequence measure for determining pairwise similarities, a novel method of evaluating gap costs, and a new iterative refinement scheme. What matters is that its implementation is highly optimized and parallelized to make the most of modern computer platforms. Thanks to the above, quality indicators, i.e. sum-of-pairs and total-column scores, show FAMSA to be superior to competing algorithms, such as Clustal Omega or MAFFT for datasets exceeding a few thousand sequences. Quality does not compromise on time or memory requirements, which are an order of magnitude lower than those in the existing solutions. For example, a family of 415519 sequences was analyzed in less than two hours and required no more than 8 GB of RAM. FAMSA is available for free at http://sun.aei.polsl.pl/REFRESH/famsa.
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