msmetaenhancer 0.2.3

Repository for tool that adds more annotations (e.g. SMILES, InChI, CAS number) to MSP files (Python version).

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, NLM, PubChem, IDSM, and BridgeDB. The app uses asynchronous implementation of annotation process allowing for optimal fetching speed.

Usage

import asyncio

from MSMetaEnhancer import Application

app = Application()

# import your .msp file
app.load_spectra('tests/test_data/sample.msp', file_format='msp')

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

# specify requested services (these are supported)
services = ['CTS', 'CIR', 'NLM', 'IDSM', 'PubChem', 'BridgeDB', '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))

# execute without jobs parameter to run all possible jobs
asyncio.run(app.annotate_spectra(services))

# export .msp file 
app.save_spectra('tests/test_data/sample_out.msp', file_format='msp')

Installation

Prerequisites:

• Python 3.7 or 3.8
• Anaconda

Install MSMetaEnhancer from Bioconda with:

# install MSMetaEnhancer in a new virtual environment to avoid dependency clashes
conda create --name MSMetaEnhancer python=3.8
conda activate MSMetaEnhancer
conda install --channel bioconda --channel conda-forge MSMetaEnhancer

Developer Documentation

Setup

Create your development environment using the provided script via conda to install all required dependencies.

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.