Confirmatory Results
Identifying accurate metagenome and amplicon software via a meta-analysis of sequence to taxonomy benchmarking studies
View ORCID ProfilePaul P. Gardner, Renee J. Watson, View ORCID ProfileXochitl C. Morgan, View ORCID ProfileJenny L. Draper, View ORCID ProfileRobert D. Finn, View ORCID ProfileSergio E. Morales, View ORCID ProfileMatthew B. Stott
doi: https://doi.org/10.1101/202077
Paul P. Gardner
1Biomolecular Interactions Centre, School of Biological Sciences, University of Canterbury, Christchurch, New Zealand.
2Department of Biochemistry, University of Otago, Dunedin, New Zealand.
Renee J. Watson
1Biomolecular Interactions Centre, School of Biological Sciences, University of Canterbury, Christchurch, New Zealand.
Xochitl C. Morgan
3Department of Microbiology and Immunology, University of Otago, Dunedin, New Zealand.
Jenny L. Draper
4Institute of Environmental Science and Research, Porirua, New Zealand.
Robert D. Finn
5European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
Sergio E. Morales
3Department of Microbiology and Immunology, University of Otago, Dunedin, New Zealand.
Matthew B. Stott
1Biomolecular Interactions Centre, School of Biological Sciences, University of Canterbury, Christchurch, New Zealand.
Article usage
Posted October 14, 2018.
Identifying accurate metagenome and amplicon software via a meta-analysis of sequence to taxonomy benchmarking studies
Paul P. Gardner, Renee J. Watson, Xochitl C. Morgan, Jenny L. Draper, Robert D. Finn, Sergio E. Morales, Matthew B. Stott
bioRxiv 202077; doi: https://doi.org/10.1101/202077
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