PT - JOURNAL ARTICLE AU - Paul P. Gardner AU - Renee J. Watson AU - Xochitl C. Morgan AU - Jenny L. Draper AU - Robert D. Finn AU - Sergio E. Morales AU - Matthew B. Stott TI - Identifying accurate metagenome and amplicon software via a meta-analysis of sequence to taxonomy benchmarking studies AID - 10.1101/202077 DP - 2018 Jan 01 TA - bioRxiv PG - 202077 4099 - http://biorxiv.org/content/early/2018/10/14/202077.short 4100 - http://biorxiv.org/content/early/2018/10/14/202077.full AB - 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 tools for analysing metagenomic and amplicon datasets, which makes selecting adequate tools a significant challenge. A number of benchmark studies have been undertaken; however, these can present conflicting results. We have applied a robust Z-score ranking procedure and a network meta-analysis method to identify software tools that are generally accurate for mapping DNA sequences to taxonomic hierarchies. Based upon these results we have identified some tools and computational strategies that produce robust predictions.