以质谱为基础的蛋白质组学中光谱质量的定义:回顾回顾。

IF 6.6 2区 化学 Q1 SPECTROSCOPY
Vilenne Frédérique, Appeltans Simon, Askenazi Manor, Valkenborg Dirk
{"title":"以质谱为基础的蛋白质组学中光谱质量的定义:回顾回顾。","authors":"Vilenne Frédérique, Appeltans Simon, Askenazi Manor, Valkenborg Dirk","doi":"10.1002/mas.21933","DOIUrl":null,"url":null,"abstract":"<p><p>Mass spectrometry-based proteomics is essential for advancing preventive and personalised medicine. Technological advancements have greatly increased both the number and sensitivity of spectra generated in a single experiment. Traditionally, spectra are identified using database search engines that depend on large and continuously expanding databases. This expansion enlarges the search space, posing challenges for controlling the false discovery rate in peptide identification. While many bioinformatic workflows employ rescoring algorithms as a post-processing step to manage false discoveries, preprocessing spectra offers a promising alternative. One such method, spectral quality assessment, classifies spectra as \"high\" quality (likely containing a peptide) or \"low\" quality (predominantly consisting of noise). This review provides a comprehensive perspective on spectral quality assessment, examining existing tools and their underlying principles. We discuss key considerations such as the definition of spectral quality, normalisation, the use of experimental training data, and future research in the field. By highlighting the potential of spectral quality assessment to improve peptide identification and reduce false discoveries, we aim to elaborate on its potential for the proteomics community.</p>","PeriodicalId":206,"journal":{"name":"Mass Spectrometry Reviews","volume":" ","pages":""},"PeriodicalIF":6.6000,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Defining Spectral Quality in Mass Spectrometry-Based Proteomics: A Retrospective Review.\",\"authors\":\"Vilenne Frédérique, Appeltans Simon, Askenazi Manor, Valkenborg Dirk\",\"doi\":\"10.1002/mas.21933\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Mass spectrometry-based proteomics is essential for advancing preventive and personalised medicine. Technological advancements have greatly increased both the number and sensitivity of spectra generated in a single experiment. Traditionally, spectra are identified using database search engines that depend on large and continuously expanding databases. This expansion enlarges the search space, posing challenges for controlling the false discovery rate in peptide identification. While many bioinformatic workflows employ rescoring algorithms as a post-processing step to manage false discoveries, preprocessing spectra offers a promising alternative. One such method, spectral quality assessment, classifies spectra as \\\"high\\\" quality (likely containing a peptide) or \\\"low\\\" quality (predominantly consisting of noise). This review provides a comprehensive perspective on spectral quality assessment, examining existing tools and their underlying principles. We discuss key considerations such as the definition of spectral quality, normalisation, the use of experimental training data, and future research in the field. By highlighting the potential of spectral quality assessment to improve peptide identification and reduce false discoveries, we aim to elaborate on its potential for the proteomics community.</p>\",\"PeriodicalId\":206,\"journal\":{\"name\":\"Mass Spectrometry Reviews\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":6.6000,\"publicationDate\":\"2025-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mass Spectrometry Reviews\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://doi.org/10.1002/mas.21933\",\"RegionNum\":2,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SPECTROSCOPY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mass Spectrometry Reviews","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1002/mas.21933","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SPECTROSCOPY","Score":null,"Total":0}
引用次数: 0

摘要

基于质谱的蛋白质组学对于推进预防和个性化医学至关重要。技术的进步大大增加了单次实验中产生的光谱的数量和灵敏度。传统上,光谱识别使用数据库搜索引擎,依赖于大型和不断扩展的数据库。这种扩展扩大了搜索空间,对控制肽识别中的错误发现率提出了挑战。虽然许多生物信息学工作流程采用评分算法作为后处理步骤来管理错误发现,但预处理光谱提供了一个有希望的替代方案。其中一种方法,光谱质量评估,将光谱分类为“高”质量(可能含有肽)或“低”质量(主要由噪声组成)。这篇综述提供了光谱质量评估的全面视角,检查了现有的工具和它们的基本原理。我们讨论了关键的考虑因素,如光谱质量的定义、归一化、实验训练数据的使用以及该领域的未来研究。通过强调光谱质量评估在改善肽鉴定和减少错误发现方面的潜力,我们的目标是详细阐述其在蛋白质组学领域的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Defining Spectral Quality in Mass Spectrometry-Based Proteomics: A Retrospective Review.

Mass spectrometry-based proteomics is essential for advancing preventive and personalised medicine. Technological advancements have greatly increased both the number and sensitivity of spectra generated in a single experiment. Traditionally, spectra are identified using database search engines that depend on large and continuously expanding databases. This expansion enlarges the search space, posing challenges for controlling the false discovery rate in peptide identification. While many bioinformatic workflows employ rescoring algorithms as a post-processing step to manage false discoveries, preprocessing spectra offers a promising alternative. One such method, spectral quality assessment, classifies spectra as "high" quality (likely containing a peptide) or "low" quality (predominantly consisting of noise). This review provides a comprehensive perspective on spectral quality assessment, examining existing tools and their underlying principles. We discuss key considerations such as the definition of spectral quality, normalisation, the use of experimental training data, and future research in the field. By highlighting the potential of spectral quality assessment to improve peptide identification and reduce false discoveries, we aim to elaborate on its potential for the proteomics community.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Mass Spectrometry Reviews
Mass Spectrometry Reviews 物理-光谱学
CiteScore
16.30
自引率
3.00%
发文量
56
期刊介绍: The aim of the journal Mass Spectrometry Reviews is to publish well-written reviews in selected topics in the various sub-fields of mass spectrometry as a means to summarize the research that has been performed in that area, to focus attention of other researchers, to critically review the published material, and to stimulate further research in that area. The scope of the published reviews include, but are not limited to topics, such as theoretical treatments, instrumental design, ionization methods, analyzers, detectors, application to the qualitative and quantitative analysis of various compounds or elements, basic ion chemistry and structure studies, ion energetic studies, and studies on biomolecules, polymers, etc.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信