第四章。PSM评分和验证

James C. Wright, J. Choudhary
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引用次数: 1

摘要

通过霰弹枪蛋白质组学实验鉴定和定量蛋白质是基于使用精确的质量和片段模式产生的串联质谱。分配肽序列串联质谱数据是由大量的信息学工具的支持。大多数光谱识别软件报告任意的适应度分数反映匹配的质量,然而,必须使用有效的统计度量来理解这些分数,并将置信度归为肽识别。准确估计误差和设计过滤程序,以尽量减少不正确和随机的识别是必不可少的,对被分析样品的生物学作出有效和可重复的结论。本章讨论了用于评估和验证散弹枪蛋白质组学肽与光谱匹配的统计方法,并提供了可用于此目的的软件摘要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Chapter 4. PSM Scoring and Validation
Identification and quantification of proteins by shotgun proteomics experiments is underpinned by the use of accurate masses and fragmentation patterns generated by tandem mass spectrometry. Assigning peptide sequences to tandem MS data is supported by a plethora of informatics tools. The majority of spectral identification software report arbitrary fitness scores reflecting the quality of a match, however, valid statistical metrics must be used to make sense of these scores and attribute a confidence to the peptide identifications. Accurately estimating the error and devising filtering routines to minimise incorrect and random identifications is essential for making valid and reproducible conclusions about the biology of the sample being analysed. This chapter discusses the statistical approaches used to evaluate and validate shotgun proteomics peptide to spectrum matches and provides a summary of software available for this purpose.
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