PLoS Computational BiologyBioinformaticsPeer-reviewed journal article
RESCRIPt: Reproducible sequence taxonomy reference database management for the masses
Michael Scott RobesoniD, Devon R. O’RourkeiD, Benjamin D. KaehleriD, Michał ZiemskiiD, Matthew R. DilloniD, Jeffrey T. FosteriD, Nicholas A. BokulichiD
Abstract
BackgroundNucleotide sequence and taxonomy reference databases are critical resources for widespread applications including marker-gene and metagenome sequencing for microbiome analysis, diet metabarcoding, and environmental DNA (eDNA) surveys. Reproducibly generating, managing, using, and evaluating nucleotide sequence and taxonomy reference databases creates a significant bottleneck for researchers aiming to generate custom sequence databases. Furthermore, database composition drastically influences results, and lack of standardizations limits cross-study comparisons. To address these challenges, we developed RESCRIPt, a software package for reproducible generation and management of reference sequence taxonomy databases, including dedicated functions that streamline creating databases from popular sources, and functions for evaluating, comparing, and interactively exploring qualitative and quantitative characteristics across reference databases. ResultsTo highlight the breadth and capabilities of RESCRIPt, we provide several examples for working with popular databases for microbiome profiling (SILVA, Greengenes, NCBI-RefSeq, GTDB), eDNA, and diet metabarcoding surveys (BOLD, GenBank), as well as for genome comparison. We show that bigger is not always better, and reference databases with standardized taxonomies and those that focus on type strains have quantitative advantages, though may not be appropriate for all use cases. Most databases appear to benefit from some curation (quality filtering), though sequence clustering appears detrimental to database quality. Finally, we demonstrate the breadth and extensibility of RESCRIPt for reproducible workflows with a comparison of global hepatitis genomes. ConclusionsRESCRIPt provides tools to democratize the process of reference database acquisition and management, enabling researchers to reproducibly and transparently create reference materials for diverse research applications. RESCRIPt is released under a permissive BSD-3 license at https://github.com/bokulich-lab/RESCRIPt.
- Citations
- 983
- FWCI
- 39.75
- Field percentile
- top 1%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- rCRUX: A Rapid and Versatile Tool for Generating Metabarcoding Reference libraries in R
Emily Curd, Luna Gal, … Zachary J. Gold·Environmental DNAPeer-reviewed·Nov 29, 2023
- A comparison between Greengenes, SILVA, RDP, and NCBI reference databases in four published microbiota datasets
Camilla Ceccarani, Marco Severgnini·bioRxiv·Apr 12, 2023
- Improving the usability and comprehensiveness of microbial databases
Caitlin Loeffler, Aaron Karlsberg, … Serghei Mangul·BMC BiologyPeer-reviewed·Apr 7, 2020
- Reference Sequence Browser: An R application with a User-Friendly GUI to rapidly query sequence databases
Sriram Ramesh, Samuel Rapp, … Zia Truong·PLoS ONEPeer-reviewed·Oct 31, 2024
- Generating, curating, and evaluating trnL reference sequence databases: Benchmarking OBITools3/ecoPCR, RESCRIPt, and MetaCurator
Ozge S Kuddar, Kelly A. Meiklejohn, Benjamin J. Callahan·bioRxiv·Apr 10, 2026
- Correcting index databases improves metagenomic studies
Guillaume Méric, Ryan R. Wick, … Michael Inouye·bioRxiv·Jul 23, 2019