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MGnify: the microbiome sequence data analysis resource in 2023.

Lorna Richardson1, Ben Allen2, Germana Baldi1

  • 1European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, UK.

Nucleic Acids Research
|December 8, 2022
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Summary
This summary is machine-generated.

The MGnify platform now offers enhanced analysis of microbiome data, including long-read sequences and deep learning-based functional annotations. It provides improved access to genomic context and downstream analysis capabilities via a Jupyter Lab environment.

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Genomics

Background:

  • The MGnify platform is a comprehensive resource for microbiome sequence data analysis and archiving.
  • It currently hosts nearly half a million analyses across various environments and sequencing types (metabarcoding, metatranscriptomics, metagenomics).

Purpose of the Study:

  • To detail recent advancements and expanded capabilities of the MGnify platform.
  • To highlight improvements in data organization, annotation depth, and user accessibility for microbiome research.

Main Methods:

  • Expansion of the MGnify protein database to over 2.4 billion non-redundant sequences.
  • Implementation of deep learning methods for advanced functional annotation.
  • Upgrade of the platform's website and Application Programming Interface (API).
  • Integration of a Jupyter Lab environment for downstream data analysis.

Main Results:

  • The MGnify protein database is now organized into a relational database, enabling navigation of genomic context.
  • Deep learning-based annotations have been applied, extending functional insights beyond previous capabilities.
  • The platform now supports analysis of long-read sequences.
  • Users can now perform downstream analyses directly within the MGnify ecosystem.

Conclusions:

  • MGnify has significantly evolved, offering a more powerful and integrated environment for microbiome data exploration.
  • The platform's advancements facilitate deeper understanding of microbial communities through improved data accessibility and analytical tools.