Structure annotation of full-scan MS data

Full-scan MS data from both LC-MS and MS imaging capture multiple ion forms, including their in/post-source fragments. Here we leverage such fragments to structurally annotate full-scan data from LC-MS or MS imaging by matching against MS/MS spectral libraries.

MS1 annotation

Workflow

Example annotations

Run the workflow

This workflow requires Python 3.9+. It has been tested on macOS (14.6, M2 Max) and Linux (Ubuntu 20.04).

• Clone the GitHub repository.

git clone git@github.com:Philipbear/ms1_id.git

• Install the dependencies. Typical installation time is <2 min.

pip install -r requirements.txt

• Run ms1id_lcms.py for LC-MS data, and ms1id_msi.py for MS imaging data.
  • An example command for LC-MS data (mzML or mzXML files in lc_ms/data folder):

    python ms1id_lcms.py --project_dir lc_ms --sample_dir data --ms1_id --ms1_id_libs data/gnps.pkl data/gnps_k10.pkl

  • An example command for MS imaging data (imzML and ibd files in msi folder):

    python ms1id_msi.py --project_dir msi --libs data/gnps.pkl data/gnps_k10.pkl

  • For more options, run python ms1id_lcms.py --help or python ms1id_msi.py --help.
• Output files will be in the project directory. MS1 annotations can be accessed from:
  • LC-MS data: aligned_feature_table.tsv
  • MS imaging data: ms1_id_annotations_derep.tsv

Expected runtime is <1 min for a single LC-MS file and <5 min for a single MS imaging dataset.

Note: Indexed libraries are needed for the workflow. You can download the indexed GNPS library here. To build your own indexed library, run index_library.py.

Citation

Shipei Xing, Vincent Charron-Lamoureux, Yasin El Abiead, Pieter C. Dorrestein. Annotating full-scan MS data using tandem MS libraries. bioRxiv 2024.

Data

• GNPS MS/MS library
  • ALL_GNPS_NO_PROPOGATED.msp, downloaded on July 17, 2024
  • Indexed version available here
• LC-MS data
  • Pooled chemical standards (GNPS/MassIVE MSV000095789)
  • NIST human feces (GNPS/MassIVE MSV000095787)
  • IBD dataset (original paper, data)
• MS imaging data
  • Mouse brain (original paper, data)
  • Mouse body (METASPACE dataset)
  • Hepatocytes (METASPACE dataset)

License

This project is licensed under the Apache 2.0 License (Copyright 2024 Shipei Xing).