Using the RDP classifier to predict taxonomic novelty and reduce the search space for finding novel organisms.

ABSTRACT:

Background

Currently, the naïve Bayesian classifier provided by the Ribosomal Database Project (RDP) is one of the most widely used tools to classify 16S rRNA sequences, mainly collected from environmental samples. We show that RDP has 97+% assignment accuracy and is fast for 250 bp and longer reads when the read originates from a taxon known to the database. Because most environmental samples will contain organisms from taxa whose 16S rRNA genes have not been previously sequenced, we aim to benchmark how well the RDP classifier and other competing methods can discriminate these novel taxa from known taxa.

Principal findings

Because each fragment is assigned a score (containing likelihood or confidence information such as the boostrap score in the RDP classifier), we "train"

SUBMITTER: Lan Y 

PROVIDER: S-EPMC3293824 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature