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Ten common issues with reference sequence databases and how to mitigate them.

Samuel D Chorlton1

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Frontiers in Bioinformatics
|April 1, 2024
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Summary

Reference sequence databases are critical for metagenomic classification but suffer from contamination and errors. This review highlights ten database issues and proposes mitigation strategies for more accurate and reproducible metagenomic analyses.

Keywords:
databasemetagenomicreferencesequencetaxonomy

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Genomics

Background:

  • Metagenomic sequencing provides insights into microbial communities.
  • Reference sequence databases are crucial for metagenomic classification.
  • Existing evaluations of metagenomic tools overlook database quality.

Purpose of the Study:

  • To review common issues in reference sequence databases for metagenomic classification.
  • To discuss the downstream consequences of these database issues.
  • To propose mitigation strategies for improving database accuracy and reproducibility.

Main Methods:

  • Literature review of issues in metagenomic reference databases.
  • Analysis of database contamination, taxonomic errors, and sequence content errors.
  • Discussion of bioinformatic tools and curation strategies for mitigation.

Main Results:

  • Identified ten common issues in reference sequence databases.
  • Highlighted pervasive problems like contamination and taxonomic errors.
  • Detailed potential downstream impacts on metagenomic study outcomes.

Conclusions:

  • Addressing reference database issues is essential for accurate metagenomic sequencing.
  • Bioinformatic tools and improved curation can mitigate database errors.
  • Implementing these strategies enhances the reproducibility and translatability of metagenomic research.