EPI2ME 25.12-01 Release

Dear Nanopore Community,

We are delighted to release a smörgåsbord of updates and improvements to our EPI2ME workflows.

Highlights include v2.0.0 of wf-bacterial-genomes (NO-MISS) with support for fungi including AMR Detection, bacterial plasmid detection with MOB-suite, and implementation of bakta. Medaka v2.2.0 is updated across our workflows bringing the latest bascalling model support.

As we approach the Christmas break, the team will be taking some well-deserved time to recharge. Rest assured that we have a magnificent collection of updates and improvements planned for the new year. Thank you for all your support.

New Releases:

• wf-aav-qc 1.3.1
  • Fixed polars.exceptions.ComputeError encountered when running the workflow under many input conditions.
  • Significant performance improvement to aav_structures step
  • Updated to Medaka 2.2.0 for performance improvements and to support data called with recent basecalling models.
• wf-amplicon 1.2.1
  • Fixed incorrect handling of numeric aliases in sample sheet
  • Updated to Medaka 2.2.0 for performance improvements and to support data called with recent basecalling models.
• wf-basecalling 1.5.7
  • Updated to Dorado 1.3.0
  • Added additional kit names for use with demultiplexing
• wf-teloseq 1.0.4
  • Improvements to basecalling helper script to support more versions of Dorado
  • Fixed counting discrepancy in filtering report table
  • Unaligned reads tagged in BAM for clearer reporting
• wf-clone-validation 1.8.4
  • Updated to support 5.2 basecaller models
  • Updated to Medaka 2.2.0 for performance improvements and to support data called with recent basecalling models.
• wf-bacterial-genomes v2.0.0
  • This update brings a range of new capabilities and improves existing analysis, detailed list of changes can be found in CHANGELOG.md, key feature changes are:
    • Genome annotation is performed using Bakta (this replaces Prokka)
    • A workflow step has been added to reorient contigs to a common stat position using Dnaapler
    • Workflow adds genome similarity based taxonomic identification through Sourmash
      • This implements GTDB R226 and NCBI Fungal reference genome databases for bacteria and fungi correspondingly
      • Users are given an option to modify the default database by providing custom exclusion list though --sourmash_db_exclude_list
    • Plasmid identification functionality has been added to the workflow by implementing MOB-suite.
      • This implements mob-recon functionality
      • This step can be optionally disabled or modified using --run_plasmid_id and --plasmid_id_opts parameters
    • Antimicrobial resistance identification functionality has been extended to include fungal AMR
      • A custom PointFinder database to include data from FungAMR database for
        • Aspergillus fumigatus
        • Canda albicans
        • Candidozyma auris
        • Nakaseomyces glabratus
        • Saccharomyces cerevisiae
      • ResFinder has been updated to v4.7.2
      • Support for specifying custom ResFinder and PointFinder databases using the --resfinder_db and --pointfinder_db parameters has been added
      • Bacterial AMR detection will now be performed for species identified through Sourmash, when MLST species call fails
      • Workflow now accepts --pointfinder_ignore_indels and --pointfinder_ignore_stop_codons ResFinder parameters
    • Medaka has been updated to v2.2.0 enabling support for v.5.2.0 basecalling data
    • Summary report has been expanded
      • A convenient summary table has been added
      • AMR section in the report has been updated to include more information and display DisinFinder data
      • The number of coverage plots displayed in the reports is now limited
        • Users can specify the maximum number of plots through --max_coverage_plots

References

1. Robertson, James, and John H E Nash. “MOB-suite: software tools for clustering, reconstruction and typing of plasmids from draft assemblies.” Microbial genomics vol. 4,8 (2018): e000206. doi:10.1099/mgen.0.000206
2. Robertson, James et al. “Universal whole-sequence-based plasmid typing and its utility to prediction of host range and epidemiological surveillance.” Microbial genomics vol. 6,10 (2020): mgen000435. doi:10.1099/mgen.0.000435
3. Irber et al., (2024). sourmash v4: A multitool to quickly search, compare, and analyze genomic and metagenomic data sets. Journal of Open Source Software, 9(98), 6830, sourmash v4: A multitool to quickly search, compare, and analyze genomic and metagenomic data sets
4. Schwengers O., Jelonek L., Dieckmann M. A., Beyvers S., Blom J., Goesmann A. (2021). Bakta: rapid and standardized annotation of bacterial genomes via alignment-free sequence identification. Microbial Genomics, 7(11). Bakta: rapid and standardized annotation of bacterial genomes via alignment-free sequence identification
5. Bédard et al. 2025. FungAMR: a comprehensive database for investigating fungal mutations associated with antimicrobial resistance. Nature Microbiology DOI 10.1038/s41564-025-02084-7.