ON USING SAMPLES OF KNOWN PROTEIN CONTENT TO ASSESS THE STATISTICAL CALIBRATION

关于使用已知蛋白质含量的样品来评估统计校准

基本信息

批准号：
8365887
负责人：
William Noble
金额：
$ 2.14万
依托单位：
UNIVERSITY OF WASHINGTON
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-09-01 至 2012-06-30
项目状态：
已结题

项目摘要

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. In shotgun proteomics, the quality of a hypothesized match between an observed spectrum and a peptide sequence is quantified by a score function. Because the score function lies at the heart of any peptide identification pipeline, this function greatly affects the final results of a proteomics assay. Consequently, valid statistical methods for assessing the quality of a given score function are extremely important. Previously, several research groups have used samples of known protein composition to assess the quality of a given score function. We demonstrate that this approach is problematic, because the outcome can depend on factors other than the score function itself. We then propose an alternative use of the same type of data to validate a score function. The central idea of our approach is that database matches that are not explained by any protein in the purified sample comprise a robust representation of incorrect matches. We apply our alternative assessment scheme to several commonly used score functions, and we show that our approach generates a reproducible measure of the calibration of a given peptide identification method. Furthermore, we show how our quality test can be useful in the development of novel score functions.

该副本是利用资源的众多研究子项目之一由NIH/NCRR资助的中心赠款提供。对该子弹的主要支持而且，副投影的主要研究员可能是其他来源提供的包括其他NIH来源。列出的总费用可能代表subproject使用的中心基础架构的估计量， NCRR赠款不直接向子弹或副本人员提供的直接资金。在shot弹枪蛋白质组学中，通过得分函数来量化观察到的光谱和肽序列之间假设匹配的质量。由于得分函数位于任何肽鉴定管道的核心，因此此功能极大地影响了蛋白质组学测定的最终结果。因此，评估给定得分功能质量的有效统计方法非常重要。以前，几个研究组使用已知蛋白质组成的样品来评估给定得分功能的质量。我们证明这种方法是有问题的，因为结果可以取决于分数功能本身以外的其他因素。然后，我们提出了相同类型数据的替代用途来验证分数函数。我们方法的核心思想是，纯化样品中任何蛋白质未解释的数据库匹配构成了不正确匹配的可靠表示。我们将替代评估方案应用于几个常用的得分功能，我们表明我们的方法生成了给定肽识别方法校准的可再现度量。此外，我们展示了我们的质量测试如何在新的分数功能的发展中有用。