bge-barcoding/BeeGees: v3.0.7

Zenodo (CERN European Organization for Nuclear Research)

Abstract

structural_validation.py now builds the barcode from every significant, non-overlapping nhmmer envelope instead of only the lowest-E-value (i.e. best) one. nhmmer reports one envelope per contiguous stretch matching the profile, so a consensus with a low-coverage hole in the middle comes back as two envelopes. parse_nhmmer_result() kept one and dropped the rest with no log line at all, truncating the barcode to whichever fragment happened to score best. Envelopes are now accepted 'greedily' in E-value order, and only where they overlap nothing already accepted in HMM and sequence coordinates. The span between envelopes is filled with N. An extra envelope is merged only when it spans more model positions than the gap it would open (i.e. is a "net gain"). The gap has no data and is filled with N's, so a small, distant envelope adds more ambiguity than sequence. Envelopes inside the accepted span cost nothing, since they convert existing N into bases, and are always merged. The best-E-value envelope remains the anchor, so no barcode can come out shorter than before the envelope net-gain fix. Replaced 01_human_cox1_filter.py with 01_human_mitogenome_filter.py, to remove human contamination by mapping reads to a human mitogenome reference and NUMTs with bwa aln instead of comparing them positionally against a hardcoded COX1 sequence. Added fasta_cleaner.human_reference to set the mapping reference. null uses the packaged human reference. fasta_cleaner.human_threshold is removed - mapping has no similarity threshold. Added the bwa_index_human_ref rule, which indexes the human reference once per run and is shared by the merge, concat and se filter rules. The index is written to resources/bwa_index/ in the working directory via bwa index -p. It is removed at the end of the run; set keep_bwa_index: true when using a genome-scale/alternative reference. Renamed the human_cox1_filter rules and the rules.human_cox1_filter resource key to human_mitogenome_filter. Output paths, file names and metric names are unchanged. MultiQC report header no longer shows the absolute path of the analysed directory (show_analysis_paths: false in multiqc_config.yaml), so server directory layouts (e.g. Galaxy job directories) are not exposed to end users. The file column of structural_validation.csv now holds paths relative to the output directory (e.g. 03_barcode_recovery/concat_mode/consensus/...) instead of absolute paths. Renamed the val_barcode_recovery_metrics_merge rule to val_barcode_recovery_metrics_combine to be more descriptive (not only a product of the 'merge' pre-processing mode). gene_fetch.type is now checked at startup with the other required gene_fetch keys, so a missing value fails immediately with a clear message instead of a KeyError when the rule is built. Declared pyyaml as a package dependency. The beegees CLI imports it to read the config, but dependencies was empty, so pip install beegees gave a CLI that failed at startup with ModuleNotFoundError: No module named 'yaml'. Conda installs were unaffected, since Snakemake pulls in pyyaml. Added .github/workflows/publish.yml: publishing a GitHub Release runs the CI tests, builds and checks the sdist and wheel, smoke-tests the installed wheel, and uploads to PyPI via Trusted Publishing.

Authors 4

1. Dan Parsons
2. Claude

   Anthropic (United States)

   Affiliation as printed

   @anthropics

3. Rutger Vos Aachen Naturalis Biodiversity Center

   Naturalis Biodiversity Center

   Affiliation as printed

   Naturalis Biodiversity Center

4. Ben Price
   Affiliation as printed

   @NaturalHistoryMuseum