MSCI

Introduction

Peptide identification by mass spectrometry relies on the interpretation of fragmentation spectra based on:

• The m/z pattern (mass-to-charge ratio),
• Relative intensities of detected fragments,
• Retention time (RT).

Given a proteome, we explored how many peptides generate highly similar fragmentation spectra with current MS methods. MSCI is a Python package built to assess the information content of peptide fragmentation spectra.

Main features

The MSCI package offers functionalities for:

• Data Import: Load proteomes and spectral libraries.
• Spectra Prediction & Processing: Predict peptide spectra and filter fragments.
• Spectra Grouping: Group peptides based on m/z and iRT values.
• Similarity Measurement: Compute spectral similarity using different scoring functions.
• Output & Visualization: Export similarity results and generate fragmentation plots.

For full API documentation, see MSCI Documentation <https://msci.readthedocs.io>_.

Usage

Example workflow:

For a full tutorial, visit our Colab notebook:
MSCI Colab Notebook <https://colab.research.google.com/drive/1ny97RNgvnpD7ZrHW8TTRXWCAQvIcavkk>_.

License

MSCI is released under the MIT License.