Release v2.5.0

[Daniel-VM]

PR checklist

• This comment contains a description of changes (with reason).
• If you've fixed a bug or added code that should be tested, add tests!
• If you've added a new tool - have you followed the pipeline conventions in the contribution docs
• If necessary, also make a PR on the nf-core/bacass branch on the nf-core/test-datasets repository.
• Make sure your code lints (nf-core pipelines lint).
• Ensure the test suite passes (nextflow run . -profile test,docker --outdir <OUTDIR>).
• Check for unexpected warnings in debug mode (nextflow run . -profile debug,test,docker --outdir <OUTDIR>).
• Usage Documentation in docs/usage.md is updated.
• Output Documentation in docs/output.md is updated.
• CHANGELOG.md is updated.
• README.md is updated (including new tool citations and authors/contributors).

PR Description

Major changes are:

• Bumped version to v2.5.0.
• Updated nf-core/bacass to nf-core 3.2.0 TEMPLATE and Template version to 3.3.2.
• Replaced download_reference.py with the NCBI Datasets API, removing the dependency on assembly_summary_refseq.txt.
• Updated modules: Unicycler (v0.5.1) and Dragonflye (v1.2.1).
• Added protein FASTA file as an optional parameter for PROKKA annotation.
• Enhanced fastq_trim_fastp_fastqc subworkflow and modules.
• Fixed CAT_FASTQ handling for long reads and hybrid assembly modes.
• Introduced LIFTOFF nf-core module and added ToulligQC for Nanopore Raw Reads.
• Added BUSCO and nf-core/filtlong modules.
• Fixed KmerFinder DB and relative path resolution issues.
• Updated Dragonflye to v1.1.2.

[Daniel-VM]

ToulligQC fails with conda due to internal errors. I have explored other versions but did not succeed. Works well with docker and singularity.

(I can add a waring in README till it gets fixed)

[Daniel-VM]

ToulligQC fails with conda due to internal errors. I have explored other versions but did not succeed. Works well with docker and singularity.

(I can add a waring in README till it gets fixed)

Seems that plotly<6 fix it.

[Daniel-VM]

Hi @d4straub , most tests are failing because Conda appears to produce flaky outputs. These errors don’t occur with Singularity or Docker. Would you consider adding the unstable Conda fields to the ignore list?

[d4straub]

From looking through some test output here, some tests (3&4) have differing md5sums, some test produce with conda additional NanoPlot png figures (e.g. 9). So there are different reasons. For differing md5sums, I'd consider removing those for the md5sum test by adding them to tests/.nftignore. The additional figures I would investigate though, thats sort of unusual.

[Daniel-VM]

Thank you, I have added the conflicting files to the ignore list in #260

[svarona]

LGTM! Good work!