Fungal identification using a Bayesian classifier and the Warcup training set of internal transcribed spacer
Vinita Deshpande1, Qiong Wang2, Paul Greenfield3
1School of Information Technologies, University of Sydney, Sydney, New South Wales, 2006, Australia.
Abstract:
Fungi are key organisms in many ecological processes and communities. Rapid and low cost surveys of the fungal members of a community can be undertaken by isolating and sequencing a taxonomically informative genomic region, such as the ITS (internal transcribed spacer), from DNA extracted from a metagenomic sample, and then classifying these sequences to determine which organisms are present. This paper announces the availability of the Warcup ITS training set and shows how it can be used with the Ribosomal Database Project (RDP) Bayesian Classifier to rapidly and accurately identify fungi using ITS sequences. The classifications can be down to species level and use conventional literature-based mycological nomenclature and taxonomic assignments.
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