Swarm: robust and fast clustering method for amplicon-based studies
Swarm: robust and fast clustering method for amplicon-based studies
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DOI：
10.7717/peerj.593
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发表时间：
2014-09-25
期刊：
影响因子：
2.7
通讯作者：
Dunthorn, Micah
中科院分区：
文献类型：
--
作者：
Mahe, Frederic;Rognes, Torbjorn;Dunthorn, Micah
流行的从头扩增子聚类方法存在两个基本缺陷：任意的全局聚类阈值和质心选择引起的输入顺序依赖性。 Swarm 的开发是为了解决这些问题，首先使用局部阈值迭代地对几乎相同的扩增子进行聚类，然后使用簇的内部结构和扩增子丰度来完善其结果。这种快速、可扩展且与输入顺序无关的方法减少了聚类参数的影响并产生强大的操作分类单元。
Popular de novo amplicon clustering methods suffer from two fundamental flaws: arbitrary global clustering thresholds, and input-order dependency induced by centroid selection. Swarm was developed to address these issues by first clustering nearly identical amplicons iteratively using a local threshold, and then by using clusters' internal structure and amplicon abundances to refine its results. This fast, scalable, and input-order independent approach reduces the influence of clustering parameters and produces robust operational taxonomic units.