Impact of training sets on classification of high-throughput bacterial 16s rRNA gene surveys
Impact of training sets on classification of high-throughput bacterial 16s rRNA gene surveys
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London: Nature Publishing Group UK
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English
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London: Nature Publishing Group UK
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Contents
Taxonomic classification of the thousands–millions of 16S rRNA gene sequences generated in microbiome studies is often achieved using a naïve Bayesian classifier (for example, the Ribosomal Database Project II (RDP) classifier), due to favorable trade-offs among automation, speed and accuracy. The resulting classification depends on the reference s...
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Impact of training sets on classification of high-throughput bacterial 16s rRNA gene surveys
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TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_3217155
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_3217155
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ISSN
1751-7362
E-ISSN
1751-7370
DOI
10.1038/ismej.2011.82
