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用于独立估计磷酸蛋白质组学假定位率的方法。

Method for Independent Estimation of the False Localization Rate for Phosphoproteomics.

机构信息

Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 3BX, U.K.

European Molecular Biology Laboratory, EMBL-European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge CB10 1SD, U.K.

出版信息

J Proteome Res. 2022 Jul 1;21(7):1603-1615. doi: 10.1021/acs.jproteome.1c00827. Epub 2022 May 31.

Abstract

Phosphoproteomic methods are commonly employed to identify and quantify phosphorylation sites on proteins. In recent years, various tools have been developed, incorporating scores or statistics related to whether a given phosphosite has been correctly identified or to estimate the global false localization rate (FLR) within a given data set for all sites reported. These scores have generally been calibrated using synthetic datasets, and their statistical reliability on real datasets is largely unknown, potentially leading to studies reporting incorrectly localized phosphosites, due to inadequate statistical control. In this work, we develop the concept of scoring modifications on a decoy amino acid, that is, one that cannot be modified, to allow for independent estimation of global FLR. We test a variety of amino acids, on both synthetic and real data sets, demonstrating that the selection can make a substantial difference to the estimated global FLR. We conclude that while several different amino acids might be appropriate, the most reliable FLR results were achieved using alanine and leucine as decoys. We propose the use of a decoy amino acid to control false reporting in the literature and in public databases that re-distribute the data. Data are available via ProteomeXchange with identifier PXD028840.

摘要

磷酸化蛋白质组学方法常用于鉴定和定量蛋白质上的磷酸化位点。近年来,已经开发出各种工具,其中包括与给定磷酸化位点是否被正确识别相关的分数或统计信息,或估计在给定数据集内所有报告的位点的全局错误定位率 (FLR)。这些分数通常使用合成数据集进行校准,而它们在真实数据集上的统计可靠性在很大程度上是未知的,这可能导致由于统计控制不足而报告错误定位的磷酸化位点的研究。在这项工作中,我们开发了在诱饵氨基酸上进行评分修饰的概念,即不能被修饰的氨基酸,以允许独立估计全局 FLR。我们在合成数据集和真实数据集上测试了多种氨基酸,证明选择可以对估计的全局 FLR 产生实质性影响。我们得出的结论是,虽然可能有几种不同的氨基酸是合适的,但使用丙氨酸和亮氨酸作为诱饵可以获得最可靠的 FLR 结果。我们建议在文献和重新分配数据的公共数据库中使用诱饵氨基酸来控制错误报告。数据可通过 ProteomeXchange 以标识符 PXD028840 获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d11f/9251759/741b25c4b1a9/pr1c00827_0002.jpg

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