NoDe: a fast error-correction algorithm for pyrosequencing amplicon reads

BMC Bioinformatics

Table 3 OTUs produced after treating the data with different noise removal approaches

The left side of the table displays the qualitative OTU assessment and the right side displays the quantitative analysis. For the qualitative analysis, we counted the number of “correct OTUs” (classified as one of the mock species), “noisy OTUs” (classified as one of mock species but only classified until Class, Order or Family level), “missed OTUs” (number of undetected mock species), “over-splitted OTUs” (correct yet redundant classification), “contaminant OTUs” (classified as species no belonging to mock) and “other OTUs” (OTUs unclassified at the Class level or higher). In the quantitative analysis, the number of OTUs with a redundancy below 0.1% (rare OTUs) and the ones with a redundancy above 0.1% (Redundant OTUs) were counted.

ISSN: 1471-2105