molamola 0.2.0

Plot Oxford Nanopore variation as self-contained HTML reports.

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A Python plotting tool for Oxford Nanopore variation data. One VCF in, one self-contained HTML report out. molamola inspects the VCF header and picks between an SV / cytogenetics report (long-read SV VCFs from Sniffles2 / cuteSV / SVIM / pbsv / NanoVar) and per-gene phased-haplotype panels (phased + VEP-annotated small-variant VCFs from WhatsHap / HiPhase). Figures embedded as base64 PNGs — no external assets, opens offline.

Full documentation: https://martinandclaude.github.io/molamola/

Install

pip install molamola

Or via conda — note that both bioconda and conda-forge channels are needed (pycirclize lives on conda-forge):

conda create -n molamola -c bioconda -c conda-forge molamola

Or for development from a clone:

git clone https://github.com/martinandclaude/molamola.git
cd molamola
pip install -e .[dev]
pytest -v

Quick start

# Long-read SV VCF (Sniffles2 etc.) → cytogenetics report
molamola --vcf sample.sniffles.vcf
open path/to/sample.report.html

# Phased + VEP-annotated VCF → compound-het workup, all candidate genes
molamola --vcf sample.phased.vep.vcf.gz
open path/to/sample.compound_het.report.html

# Just one gene from a phased + VEP VCF
molamola --vcf sample.phased.vep.vcf.gz --gene NEB

The plot type is auto-detected from the VCF header: ##INFO=<ID=SVTYPE> selects SV mode; ##INFO=<ID=CSQ> + ##FORMAT=<ID=PS> selects compound-het mode. VCFs that match neither shape are refused with a clear error.

See the docs for example output, VEP annotation prep, the full CLI reference, filter explanations, and worked examples.

Acknowledgements

• Sniffles2, cuteSV, SVIM, pbsv, NanoVar — long-read SV callers.
• WhatsHap, HiPhase — long-read phasing.
• VEP, MANE Select, ClinVar — variant annotation and significance.
• pyCirclize — circos plot.
• matplotlib, numpy.
• bcftools / samtools / htslib — VCF pre-processing helpers.
• UCSC Genome Browser — hg38 and T2T-CHM13v2.0 cytobands.
• iconsdb.com — header fish icon (deep-pink, mirrored).

License

MIT.