MSCI assesses peptide fragmentation spectra information content.
Project description
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.
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