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.
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.
Example workflow:
For a full tutorial, visit our Colab notebook: MSCI Colab Notebook.
MSCI is released under the MIT License.