A novel conceptual approach to read-filtering in high-throughput amplicon sequencing studies.

ABSTRACT: Adequate read filtering is critical when processing high-throughput data in marker-gene-based studies. Sequencing errors can cause the mis-clustering of otherwise similar reads, artificially increasing the number of retrieved Operational Taxonomic Units (OTUs) and therefore leading to the overestimation of microbial diversity. Sequencing errors will also result in OTUs that are not accurate reconstructions of the original biological sequences. Herein we present the Poisson binomial filtering algorithm (PBF), which minimizes both problems by calculating the error-probability distribution of a sequence from its quality scores. In order to validate our method, we quality-filtered 37 publicly available datasets obtained by sequencing mock and environmental microbial communities with the Roche

SUBMITTER: Puente-Sanchez F 

PROVIDER: S-EPMC4770208 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature