MSCI: an open-source Python package for information content assessment of peptide fragmentation spectra

TL;DR

MSCI is a Python tool that helps identify hard-to-distinguish peptides in mass spectrometry data for better proteomics analysis.

Contribution

MSCI introduces a new open-source Python package for evaluating fragmentation similarity and identifying indistinguishable peptides.

Findings

MSCI streamlines the workflow from data import to spectral analysis in proteomics.

The tool enables effective evaluation of fragmentation similarity scores among peptides.

It helps identify indistinguishable peptide pairs within a proteome.

Abstract

In mass spectrometry-based proteomics, the availability of peptide prior knowledge has improved our ability to assign fragmentation spectra to specific peptide sequences. However, some peptides exhibit similar analytical values and fragmentation patterns, which makes them nearly indistinguishable with current data analysis tools.

Here we developed the Mass Spectrometry Content Information (MSCI) Python package to tackle the challenges of peptide identification in mass spectrometry-based proteomics, particularly regarding indistinguishable peptides. MSCI provides a comprehensive toolset that streamlines the workflow from data import to spectral analysis, enabling researchers to effectively evaluate fragmentation similarity scores among peptide sequences and pinpoint indistinguishable peptide pairs in a given proteome.

MSCI is implemented in Python and it is released under a permissive MIT license. The source code and the installers are available on GitHub at https://github.com/proteomicsunitcrg/MSCI.

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