一般化前体预测提高了基于质谱的蛋白质组学识别率和准确性
Aaron M Scott1, Christofer Karlsson2, Tirthankar Mohanty2
1Division of Infection Medicine, Department of Clinical Sciences, Lund University, Lund, Sweden. aaron.scott@med.lu.se.
Communications biology
|June 10, 2023
概括
我们开发了一种通用前体评分 (GPS) 方法,使用数据独立采集质谱法 (DIA-MS) 改进生物标志物发现. 这种方法增强了蛋白质识别,并控制了错误发现率 (FDR),以准确地分析基于血液的生物标记.
科学领域:
- 蛋白质组学是指蛋白质组学.
- 生物标志物发现发现
- 质谱测量质量谱测量
背景情况:
- 数据独立采集质谱 (DIA-MS) 对基于血液的生物标志物识别有价值.
- 血蛋白质组分析中的大搜索空间可能会导致错误阳性,并损害错误发现率 (FDR) 的准确性.
研究的目的:
- 开发一种用于控制FDR和增加DIA-MS中蛋白质识别的新方法.
- 提高DIA-MS用于生物标志物发现的准确性和通用性.
主要方法:
- 开发了一种通用前体评分 (GPS) 方法,对275万个前体进行训练.
- 应用GPS到DIA-MS数据用于血蛋白质组分析.
- 在新数据集和生物标志物识别上验证了GPS性能.
主要成果:
- GPS可靠地控制FDR,同时增加DIA-MS中的蛋白质识别率.
- GPS证明了对新数据集的概括性,并提高了定量准确性.
- 使用GPS识别了一组基于血液的蛋白质生物标志物,用于性急性损伤亚表型.
结论:
- 通用前体评分 (GPS) 方法提高了DIA-MS在生物标志物发现方面的性能.
- GPS提供了一种强大的方法来控制FDR,并在复杂的蛋白质组样本中增加蛋白质识别.
- 全球定位系统有助于精确识别基于血液的生物标志物,正如性急性损伤亚表型歧视所示.
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