DySC: software for greedy clustering of 16S rRNA reads.

Zheng, Zejun; Kramer, Stefan; Schmidt, Bertil · Bioinformatics · 2012

other · Level V

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Abstract

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. DySC, implemented in C, is available at http://code.google.com/p/dysc/ under GNU GPL license.

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