MSCI:一个开源的Python包,用于肽片段谱的信息内容评估。

IF 2.8 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Bioinformatics advances Pub Date : 2025-05-24 eCollection Date: 2025-01-01 DOI:10.1093/bioadv/vbaf125
Zahra Elhamraoui, Eva Borràs, Mathias Wilhelm, Eduard Sabidó
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引用次数: 0

摘要

动机:在基于质谱的蛋白质组学中,肽先验知识的可用性提高了我们将片段谱分配给特定肽序列的能力。然而,一些肽表现出相似的分析值和片段模式,这使得它们几乎无法用当前的数据分析工具进行区分。结果:在这里,我们开发了质谱内容信息(MSCI) Python包来解决基于质谱的蛋白质组学中肽鉴定的挑战,特别是关于不可区分的肽。MSCI提供了一个全面的工具集,简化了从数据导入到光谱分析的工作流程,使研究人员能够有效地评估肽序列之间的片段相似性评分,并确定给定蛋白质组中不可区分的肽对。可用性和实现:MSCI是用Python实现的,它是在一个宽松的MIT许可下发布的。源代码和安装程序可在GitHub上获得https://github.com/proteomicsunitcrg/MSCI。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MSCI: an open-source Python package for information content assessment of peptide fragmentation spectra.

Motivation: 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.

Results: 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.

Availability and implementation: 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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CiteScore
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