omicsmeta is an early-stage Python package for harmonizing public omics
metadata from GEO, SRA, BioSample, and tabular exports.
The central design choice is to make ontology mapping pluggable. Generic
mapping tools such as text2term are useful, but public omics metadata also
needs domain-specific preprocessing, field-type detection, confidence-aware
routing, and cross-field validation. omicsmeta is intended to provide that
pipeline.
Current implementation status:
- string normalization and biomedical abbreviation expansion
- heuristic metadata field detection
- lightweight built-in ontology mapper for common terms
- optional
text2termmapper adapter - simple OBO loader and SQLite ontology cache
- tabular, minimal GEO SOFT, BioSample XML, and SRA XML readers
- harmonization orchestrator and CLI
- real GEO SOFT snippet test coverage
- conservative field routing for ambiguous metadata columns
- transparent cell-line inference for missing species/tissue/disease fields
- deduplicated unmapped-term summaries for manual curation
- sample-wide output tables
- batch harmonization
- known-answer benchmark helper and CLI script
Example:
omicsmeta harmonize metadata.tsv \
--output harmonized.tsv \
--unmapped unmapped.tsv \
--unmapped-summary-output unmapped_summary.tsv \
--sample-output samples.tsv \
--report qc_report.htmlDirect GEO fetching is also available:
omicsmeta harmonize \
--geo-accession GSE123456 \
--output harmonized.tsv \
--unmapped unmapped.tsv \
--unmapped-summary-output unmapped_summary.tsv \
--sample-output samples.tsv \
--report qc_report.htmlCustom local OBO files can be added to the built-in mapper:
omicsmeta harmonize metadata.tsv \
--ontology-obo disease_slim.obo \
--output harmonized.tsv \
--unmapped unmapped.tsv \
--unmapped-summary-output unmapped_summary.tsv \
--sample-output samples.tsv \
--report qc_report.htmlManaged ontology resources can be cached locally:
omicsmeta ontologies list
omicsmeta ontologies download doid uberon cl
omicsmeta ontologies index --resource doid --resource uberon
omicsmeta harmonize metadata.tsv \
--ontology-resource doid \
--ontology-resource uberon \
--output harmonized.tsv \
--unmapped unmapped.tsv \
--unmapped-summary-output unmapped_summary.tsv \
--sample-output samples.tsv \
--report qc_report.htmlMultiple files can be harmonized in one run:
omicsmeta batch \
--input metadata_a.tsv \
--input metadata_b.tsv \
--output harmonized.tsv \
--unmapped unmapped.tsv \
--unmapped-summary-output unmapped_summary.tsv \
--sample-output samples.tsv \
--report qc_report.htmlKnown-answer fixtures can be benchmarked:
python scripts/benchmark_mapping.py \
--input examples/basic/metadata.tsv \
--truth examples/basic/expected_harmonized.tsvRun the bundled multi-fixture benchmark suite:
python scripts/benchmark_mapping.py \
--manifest benchmarks/known_answer_suite.tsv \
--output-json benchmark_suite.jsonThis repository is pre-alpha and not yet JOSS-ready. The implemented code is tested, but the project still needs publication-scale curated benchmarks, release packaging, external user feedback, and Galaxy Tool Shed validation before submission.
Run tests locally with:
python -m pip install -e ".[dev]"
python -m pytest