Impact of training sets on classification of high-throughput bacterial 16s rRNA gene surveys

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 r...

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書誌詳細
主要な著者: Werner, Jeffrey J, Koren, Omry, Hugenholtz, Philip, DeSantis, Todd Z, Walters, William A, Caporaso, J Gregory, Angenent, Largus T, Knight, Rob, Ley, Ruth E
フォーマット: Artigo
言語:Inglês
出版事項: Nature Publishing Group 2012
主題:
Original Article
オンライン･アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC3217155/
https://ncbi.nlm.nih.gov/pubmed/21716311
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/ismej.2011.82
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