Facilitating bioinformatics reproducibility with QIIME 2 Provenance Replay.

Autor: Keefe CR; Center for Applied Microbiome Science, Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, United States of America., Dillon MR; Center for Applied Microbiome Science, Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, United States of America., Gehret E; Center for Applied Microbiome Science, Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, United States of America., Herman C; Center for Applied Microbiome Science, Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, United States of America.; School of Informatics, Computing and Cyber Systems, Northern Arizona University, Flagstaff, Arizona, United States of America., Jewell M; Department of Epidemiology, University of Washington, Seattle, Washington, United States of America., Wood CV; Center for Applied Microbiome Science, Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, United States of America., Bolyen E; Center for Applied Microbiome Science, Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, United States of America., Caporaso JG; Center for Applied Microbiome Science, Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, United States of America.; School of Informatics, Computing and Cyber Systems, Northern Arizona University, Flagstaff, Arizona, United States of America.
Jazyk: angličtina
Zdroj: PLoS computational biology [PLoS Comput Biol] 2023 Nov 27; Vol. 19 (11), pp. e1011676. Date of Electronic Publication: 2023 Nov 27 (Print Publication: 2023).
DOI: 10.1371/journal.pcbi.1011676
Abstrakt: Study reproducibility is essential to corroborate, build on, and learn from the results of scientific research but is notoriously challenging in bioinformatics, which often involves large data sets and complex analytic workflows involving many different tools. Additionally, many biologists are not trained in how to effectively record their bioinformatics analysis steps to ensure reproducibility, so critical information is often missing. Software tools used in bioinformatics can automate provenance tracking of the results they generate, removing most barriers to bioinformatics reproducibility. Here we present an implementation of that idea, Provenance Replay, a tool for generating new executable code from results generated with the QIIME 2 bioinformatics platform, and discuss considerations for bioinformatics developers who wish to implement similar functionality in their software.
Competing Interests: The authors have declared that no competing interests exist.
(Copyright: © 2023 Keefe et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Databáze: MEDLINE
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