Cross Domain Metadata Harmonization

cross-domain-metadata-harmonization

License: restricted — no clear open-source license detected for the underlying tool; verify licensing before commercial use or redistribution.

Summary

Aggregates and normalizes heterogeneous mass spectrometry search results from multiple domain-specific MASST tools (microbe, plant, tissue, microbiome, food) into a unified data structure for integrated visualization and comparative analysis. This skill enables unified querying across disparate taxonomic and sample-type domains without manual result consolidation.

When to use

When you have submitted the same MS/MS spectrum query to multiple domain-specific MASST tools and need to compare matches, combine ranked results, or generate cross-domain summary statistics. Specifically applicable when batch-searching multiple spectra across all domainMASSTs simultaneously using the Fast Search API and requiring harmonized outputs for downstream interpretation.

When NOT to use

• Searching spectra within a single domain only—use the standalone domain-specific MASST tool directly (e.g., microbeMASST alone) for faster single-domain queries
• When your input spectra are already pre-filtered to a single biological domain and cross-domain comparison adds no interpretive value
• If you require real-time single-spectrum search feedback; batch aggregation via jobs.py is designed for bulk processing and may incur API latency

Inputs

• MS/MS spectra in .mgf format (from MZmine or GNPS molecular networking)
• Batch lists of Universal Spectrum Identifiers (USIs) in .csv or .tsv format
• JSON search result objects from individual domain-specific MASST API endpoints
• Search parameters (cosine score threshold, m/z tolerance, minimum matching peaks)

Outputs

• Interactive HTML tree files per domain (_microbe.html, _plant.html, etc.)
• Domain-specific JSON tree objects (_microbe.json, _plant.json, etc.)
• _matches.tsv: unified list of all matching spectra across all indexed databases with domain origin
• _library.tsv: GNPS library matches supporting Level 2 metabolomics annotation
• _datasets.tsv: counts of unique samples per indexed dataset matching the query
• _count_domain.tsv files: match counts and metadata per individual domain MASST
• Aggregated visualization object suitable for metadataMASST web interface

How to apply

Clone the GNPS_MASST and robinschmid/microbe_masst repositories to access the base framework and metadataMASST component code. Route search results from each domain-specific MASST (microbeMASST, plantMASST, tissueMASST, microbiomeMASST, foodMASST) through a unified aggregation layer by normalizing input schemas—converting heterogeneous API responses into a common data model. Implement aggregation logic that combines results while preserving domain origin metadata (e.g., '_microbe.json', '_plant.json' annotations). Set search parameters consistently across domains: minimum cosine score, m/z tolerance, and minimum matching peaks thresholds. Generate normalized outputs including _matches.tsv (all spectrum matches across indexed databases), _library.tsv (GNPS library matches for Level 2 annotations), _datasets.tsv (unique sample counts per dataset), and domain-specific _count_domain.tsv files. Validate end-to-end by comparing individual domain outputs against the aggregated metadataMASST visualization to ensure no loss or duplication of matches.

Related tools

• GNPS_MASST (Base framework housing all standalone domain-specific MASST web applications and aggregation layer code) — https://github.com/mwang87/GNPS_MASST
• metadataMASST (Web application endpoint that visualizes and renders aggregated cross-domain search results) — https://masst.gnps2.org/metadatamasst/
• microbeMASST (Domain-specific search tool queried for microbial metabolite matches; results aggregated via this skill) — https://masst.gnps2.org/microbemasst/
• plantMASST (Domain-specific search tool queried for plant metabolite matches; results aggregated via this skill) — https://masst.gnps2.org/plantmasst/
• tissueMASST (Domain-specific search tool queried for tissue metabolite matches; results aggregated via this skill) — https://masst.gnps2.org/tissuemasst/
• microbiomeMASST (Domain-specific search tool queried for microbiome metabolite matches; results aggregated via this skill) — https://masst.gnps2.org/microbiomemasst/
• foodMASST (Domain-specific search tool queried for food metabolite matches; results aggregated via this skill) — https://masst.gnps2.org/foodmasst2/
• Fast Search API (Backend search service invoked by jobs.py for batch querying against indexed GNPS/MassIVE, Metabolomics Workbench, Metabolights, and NORMAN databases) — https://fasst.gnps2.org/fastsearch/
• jobs.py (Batch orchestration script that coordinates multi-spectrum queries across all domainMASSTs and triggers aggregation workflow) — https://github.com/robinschmid/microbe_masst/blob/master/code/jobs.py

Examples

python jobs.py  # After adding entries to files list as ("input_dir/spectra.mgf", "output_dir/results"), then inspect output_dir/results_matches.tsv, output_dir/results_library.tsv, and output_dir/results_microbe.html for aggregated cross-domain results

Evaluation signals

• Verify that the count of unique spectrum matches in _matches.tsv equals or exceeds the union of individual domain-specific _count_domain.tsv files (no duplicates within a domain, no losses across domains)
• Confirm that all _matches.tsv rows have non-null 'domain_origin' annotations and that each row traces back to at least one valid source domain HTML/JSON file
• Check that Level 2 annotations in _library.tsv correspond to GNPS library entries and that the count of library matches is monotonically consistent when re-running the same batch (idempotency check via skip_existing=True)
• Validate that _datasets.tsv reports sample counts per indexed dataset (GNPS/MassIVE, Metabolomics Workbench, Metabolights, NORMAN) and that the sum of counts across datasets in a domain-specific _count_domain.tsv is non-zero
• Re-run jobs.py multiple times with skip_existing=True and confirm that no new output is generated after the second or third iteration (convergence of Fast Search API results)

Limitations

• The Fast Search API may fail to return results for some spectrum entries on first execution; sequential re-runs with skip_existing=True are required to achieve complete coverage, and success is not guaranteed for all entries
• Aggregation depends on consistent indexing of all source databases (GNPS/MassIVE, Metabolomics Workbench, Metabolights, NORMAN); if a database is offline or out-of-sync, matches from that source will be missing from _matches.tsv without explicit warning
• Batch search requires Python 3.10; compatibility with other Python versions is not tested and may result in API client failures
• Cross-domain aggregation preserves all matches found in the indexed data, including spectra outside the curated domain-specific MASST lineages; filtering to curated-only results requires post-processing against the lineage TSV files provided in the repository

Evidence

• [readme] Aggregated search outputs can be generated and visualized using metadataMASST: "Aggregated search outputs can be generated and visualized using metadataMASST"
• [readme] Running jobs.py allows users to leverage the Fast Search API and execute a batch search of multiple MS/MS spectra against the current indexed data in GNPS/MassIVE, Metabolomics Workbench, Metabolights, and NORMAN: "Running jobs.py allows users to leverage the Fast Search API and execute a batch search"
• [other] Implement aggregation logic to combine heterogeneous search outputs from all domain sources into a single normalized data structure: "Implement aggregation logic to combine heterogeneous search outputs from all domain sources into a single normalized data structure"
• [readme] A _matches.tsv file will be generated. This contains all the scans found to match your searched spectrum of interest in the data that have been currently indexed.: "A _matches.tsv file will be generated. This contains all the scans found to match your searched spectrum of interest in the data that have been currently indexed"
• [readme] A _library.tsv file will be generated enabling a Level 2 annotation according the Metabolomics Standards Initiative: "A _library.tsv file will be generated. This contains a list of spectra from the GNPS libraries found to match your spectrum of interest. This enables a Level 2"
• [readme] Make sure to run jobs.py a couple of times, until no new output is generated by having the option skip_existing=True. Due to the Fast Search API some of the entries will fail.: "Make sure to run jobs.py a couple of times, until no new output is generated by having the option: skip_existing=True."
• [other] metadataMASST enables generation and visualization of aggregated search outputs across domain-specific MASST searches: "metadataMASST enables generation and visualization of aggregated search outputs across domain-specific MASST searches, distinguishing it from standalone tools that search one spectrum at a time"