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Application of database-independent approach to assess the quality of OTU picking methods

View ORCID ProfilePatrick D. Schloss
doi: https://doi.org/10.1101/042812
Patrick D. Schloss
Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI
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  • For correspondence: pschloss@umich.edu
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Abstract

Assigning 16S rRNA gene sequences to operational taxonomic units (OTUs) allows microbial ecologists to overcome the inconsistencies and biases within bacterial taxonomy and provides a strategy for clustering similar sequences that do not have representatives in a reference database. I have applied the Matthew’s correlation coefficient to assess the ability of 15 reference-independent and-dependent clustering algorithms to assign sequences to OTUs. This metric quantifies the ability of an algorithm to reflect the relationships between sequences without the use of a reference and can be applied to any dataset or method. The most consistently robust method was the average neighbor algorithm; however, for some datasets other algorithms matched its performance.

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Posted March 08, 2016.
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Application of database-independent approach to assess the quality of OTU picking methods
Patrick D. Schloss
bioRxiv 042812; doi: https://doi.org/10.1101/042812
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Application of database-independent approach to assess the quality of OTU picking methods
Patrick D. Schloss
bioRxiv 042812; doi: https://doi.org/10.1101/042812

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