Nguyen Thuy-Diem

Efficient and accurate OTU clustering with GPU-based sequence alignment and dynamic dendrogram cutting

Published date : 05 Oct 2015

De novo clustering is a popular technique to perform taxonomic profiling of a microbial community by grouping 16S rRNA amplicon reads into operational taxonomic units (OTUs). In this work, we introduce a new dendrogram-based OTU clustering pipeline called CRiSPy. The key idea used in CRiSPy to improve clustering accuracy is the application of an anomaly detection technique to obtain a dynamic distance cutoff instead of using the de facto value of 97 percent sequence similarity as in most existing OTU

Journal Paper
IEEE/ACM Transactions on Computation Biology and Bioinformatics, Vol. 12, No. 5, Sept/Oct 2015
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