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Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
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THAPBI PICT-a fast, cautious, and accurate metabarcoding analysis pipeline.

Peter J A Cock1, David E L Cooke2, Peter Thorpe2,3

  • 1Information and Computational Sciences, The James Hutton Institute, Dundee, United Kingdom.

Peerj
|August 23, 2023
PubMed
Summary

THAPBI PICT is an open-source metabarcoding software for analyzing Illumina paired-end reads. This versatile tool, initially for Phytophthora, can be adapted for various amplicons and organisms, simplifying complex data analysis.

Keywords:
AmpliconBarcodingBiodiversityEnvironmental DNAMetabarcodingPhytophthora

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Metabarcoding analysis of environmental DNA (eDNA) is crucial for biodiversity assessment.
  • Existing pipelines often require specialized configurations for different marker genes and organisms.
  • Handling multiplexed amplicons and noisy sequence data presents analytical challenges.

Purpose of the Study:

  • To introduce THAPBI PICT, a flexible open-source software pipeline for metabarcoding analysis.
  • To demonstrate the adaptability of THAPBI PICT for diverse amplicons, organisms, and datasets beyond its initial scope.
  • To provide a user-friendly tool for non-specialists to interpret metabarcoding results.

Main Methods:

  • Data reduction to Amplicon Sequence Variants (ASVs) from Illumina paired-end reads.
  • Application of dynamic abundance thresholds for noise and artifact removal.
  • Classification of ASVs against curated reference databases with flexible matching criteria.

Main Results:

  • THAPBI PICT successfully processes multiplexed samples and various amplicons with appropriate settings.
  • The pipeline effectively identifies ASVs and classifies them based on user-defined or automated abundance thresholds.
  • Generated outputs include detailed read and sample reports, along with ASV topological graphs for interpretation.

Conclusions:

  • THAPBI PICT offers a robust and adaptable solution for metabarcoding analysis, enhancing accessibility for researchers.
  • The software's modular design allows for broad application across different ecological and biological studies.
  • Availability of source code and documentation facilitates widespread adoption and further development.