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Identifying accurate metagenome and amplicon software via a meta-analysis of sequence to taxonomy benchmarking studies

By Paul P. Gardner, Renee J. Watson, Xochitl C. Morgan, Jenny L. Draper, Robert D. Finn, Sergio E. Morales, Matthew B. Stott

Posted 12 Oct 2017
bioRxiv DOI: 10.1101/202077 (published DOI: 10.7717/peerj.6160)

Environmental DNA sequencing has rapidly become a widely-used technique for investigating a range of questions, particularly related to health and environmental monitoring. There has also been a proliferation of bioinformatic methods for analysing metagenomic and amplicon datasets, which makes selecting adequate methods a significant challenge. A number of benchmark studies have been undertaken; however, these often present conflicting results. We have applied a network meta-analysis method to identify software methods that are generally accurate for mapping DNA sequences to taxonomic hierarchies. Based upon these results we have identified some methods and computational strategies that produce robust predictions.

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