GSR-DB: a manually curated and optimized taxonomical database for 16S rRNA amplicon analysis

  • Molano L
  • Vega-Abellaneda S
  • Manichanh C
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Abstract

Taxonomic assignments of microorganisms have long been hindered by inconsistent nomenclature and annotation issues in existing databases like SILVA, Greengenes, Greengenes2, Genome Taxonomy Database, or Ribosomal Database Project. To overcome these issues, we created Greengenes-SILVA-RDP database (GSR-DB), accurate and comprehensive taxonomic annotations of 16S amplicon data. Unlike previous approaches, our innovative pipeline includes a unique taxonomy unification step, ensuring consistent and reliable annotations. Our evaluation analyses showed that GSR-DB outperforms existing databases in providing species-level resolution, especially based on mock-community analysis, making it a game-changer for microbiome studies. Moreover, GSR-DB is designed to be accessible to researchers with limited computational resources, making it a powerful tool for scientists across the board. Available for full-length 16S sequences and commonly used hypervariable regions, including V4, V1–V3, V3–V4, and V3–V5, GSR-DB is a go-to database for robust and accurate microbial taxonomy analysis.

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Molano, L.-A. G., Vega-Abellaneda, S., & Manichanh, C. (2024). GSR-DB: a manually curated and optimized taxonomical database for 16S rRNA amplicon analysis. MSystems, 9(2). https://doi.org/10.1128/msystems.00950-23

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