DySC: software for greedy clustering of 16S rRNA reads | Zendy

Zejun Zheng | Zendy; Stefan Krämer | Zendy; Bertil Schmidt | Zendy

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DySC: software for greedy clustering of 16S rRNA reads

Author(s) -

Zejun Zheng,

Stefan Krämer,

Bertil Schmidt

Publication year - 2012

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bts355

Subject(s) - cluster analysis , mit license , computer science , software , greedy algorithm , pyrosequencing , data mining , computational biology , biology , artificial intelligence , gene , genetics , algorithm , programming language

Pyrosequencing technologies are frequently used for sequencing the 16S ribosomal RNA marker gene for profiling microbial communities. Clustering of the produced reads is an important but time-consuming task. We present Dynamic Seed-based Clustering (DySC), a new tool based on the greedy clustering approach that uses a dynamic seeding strategy. Evaluations based on the normalized mutual information (NMI) criterion show that DySC produces higher quality clusters than UCLUST and CD-HIT at a comparable runtime.

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