Elhamraoui Zahra, Borràs Eva, Wilhelm Mathias, Sabidó Eduard
Proteomics Unit, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, 08003, Spain.
Proteomics Unit, University Pompeu Fabra (UPF), Barcelona, 08003, Spain.
Bioinform Adv. 2025 May 24;5(1):vbaf125. doi: 10.1093/bioadv/vbaf125. eCollection 2025.
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.
在基于质谱的蛋白质组学中，肽段先验知识的可用性提高了我们将碎裂谱分配给特定肽段序列的能力。然而，一些肽段表现出相似的分析值和碎裂模式，这使得它们在当前数据分析工具下几乎无法区分。
在此，我们开发了质谱内容信息（MSCI）Python软件包，以应对基于质谱的蛋白质组学中肽段鉴定的挑战，特别是关于难以区分的肽段。MSCI提供了一套全面的工具集，简化了从数据导入到谱图分析的工作流程，使研究人员能够有效评估肽段序列之间的碎裂相似性得分，并在给定的蛋白质组中找出难以区分的肽段对。
MSCI用Python实现，并在宽松的MIT许可下发布。源代码和安装程序可在GitHub上获取，网址为https://github.com/proteomicsunitcrg/MSCI。
