MSMetaEnhancer

MSMetaEnhancer is a tool used for .msp files annotation. It adds metadata like SMILES, InChI, and CAS number fetched from the following services: CIR, CTS, PubChem, IDSM, BridgeDb, Wikidata, and ChEBI. The app uses asynchronous implementation of annotation process allowing for optimal fetching speed.

If you use MSMetaEnhancer in your work, please cite the following publication:

Troják et al., (2022). MSMetaEnhancer: A Python package for mass spectra metadata annotation. Journal of Open Source Software, 7(79), 4494, https://doi.org/10.21105/joss.04494

Usage

import asyncio

from MSMetaEnhancer import Application
from MSMetaEnhancer.libs.converters.web import (
    CTS,
    CIR,
    IDSM,
    PubChem,
    BridgeDb,
    Wikidata,
    ChEBI,
)
from MSMetaEnhancer.libs.converters.compute import RDKit
from MSMetaEnhancer.libs.utils.ConverterBuilder import ConverterBuilder

ConverterBuilder.register([CTS, CIR, IDSM, PubChem, BridgeDb, Wikidata, ChEBI, RDKit])

app = Application()

# import your .msp file
app.load_data('sample.msp', file_format='msp')

# curate given metadata (e.g. fix CAS numbers)
app.curate_metadata()

# specify requested services (these are supported)
services = ['CTS', 'CIR', 'IDSM', 'PubChem', 'BridgeDb', 'Wikidata', 'ChEBI', 'RDKit']

# specify requested jobs
jobs = [('name', 'inchi', 'IDSM'), ('inchi', 'formula', 'IDSM'), ('inchi', 'inchikey', 'IDSM'),
        ('inchi', 'iupac_name', 'IDSM'), ('inchi', 'canonical_smiles', 'IDSM')]

# run asynchronous annotations of spectra data
asyncio.run(app.annotate_spectra(services, jobs))

# export .msp file
app.save_data('sample_out.msp', file_format='msp')

Installation

Prerequisites:

• Python 3.10 - 3.13

Install MSMetaEnhancer from Bioconda with:

# install MSMetaEnhancer in a new virtual environment to avoid dependency clashes
conda create --name MSMetaEnhancer python=3.12
conda activate MSMetaEnhancer
conda install --channel bioconda --channel conda-forge MSMetaEnhancer

Alternatively, install it from PyPI into any environment of your choice:

pip install msmetaenhancer

Developer Documentation

Setup

Development dependencies, the virtual environment and the package itself are all managed by uv. Install uv once (e.g. pip install uv, or conda install --channel conda-forge uv), clone the repository and run:

uv sync

This creates .venv in the repository root, installs the locked dependencies together with the dev group, and installs MSMetaEnhancer in editable mode. A conda environment can still be created from the provided script if you prefer conda; it provides uv and Python, and uv sync then fills in the rest.

Run everything through uv run so that it uses this environment:

uv run pytest                                          # tests
uv run ruff check .                                    # lint
uv run pre-commit install                              # git hooks
uv run --group docs sphinx-build -b html docs/source docs/build/html   # documentation

Dependencies are pinned in the committed uv.lock. After changing the dependencies in pyproject.toml, refresh the lock with uv lock and reinstall with uv sync — CI installs with uv sync --frozen and therefore fails if the two are out of sync.

Contributing

We appreciate contributions - feel free to open an issue on our repository, create your own fork, work on the problem and post a PR. Please add your contributions to the changelog and to adhere to the versioning. For more information see here.

Testing

All functionality is tested with the pytest framework. Run the test suite with uv run pytest.