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Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

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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Updated: Jun 27, 2026

Introductory Analysis and Validation of CUT&#38;RUN Sequencing Data
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Published on: December 13, 2024

MGtree: A Fast and Flexible Alignment-Based Metagenomics Pipeline.

Samantha L Sholes1, Scott Norton2, Alfredo Gonzalez2

  • 1Department of Data Science & Scientific Informatics, MRL-Information Technology, Merck & Co., Inc., West Point, PA 19486, USA.

Viruses
|June 26, 2026
PubMed
Summary
This summary is machine-generated.

MGtree is a new metagenomics pipeline that accurately identifies viral samples using full-length read alignments and phylogenetic analysis. It improves classification precision for complex samples, outperforming existing tools like Kraken2 and Centrifuge.

Keywords:
HPVmetagenomicsnorovirusphylogeneticsshort read alignment

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Area of Science:

  • Bioinformatics
  • Virology
  • Genomics

Background:

  • Metagenomics analysis is vital for viral identification and typing in surveillance and clinical settings.
  • Current methods face limitations in taxonomic resolution and accuracy with complex or recombinant viral samples.

Purpose of the Study:

  • To introduce MGtree, a novel metagenomics pipeline designed for enhanced viral sample classification.
  • To evaluate MGtree's performance against existing tools and in challenging sample types.

Main Methods:

  • MGtree employs a combination of full-length read alignments and phylogenetic analysis for sample classification.
  • The pipeline was tested on challenging norovirus and human papillomavirus (HPV) datasets, including low-input and coinfected samples.

Main Results:

  • MGtree accurately genotypes viral samples, demonstrating superior performance compared to Kraken2 and Centrifuge.
  • The pipeline successfully classifies low-input samples where de novo assembly fails.
  • MGtree shows high precision in resolving genotypes from highly mutant and coinfected samples.

Conclusions:

  • MGtree offers improved viral genotype resolution and classification precision, particularly for complex metagenomic samples.
  • This novel pipeline has the potential to enhance viral surveillance and clinical diagnostics.