{"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}
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.
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.