Targeted Feature Detection and Extraction

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在数据依赖采集（data-dependent acquisition, DDA）蛋白质组学实验中，肽段鉴定漏检问题会阻碍精准判定样本中所含蛋白质种类及其相对丰度。现有研究尝试依托原始数据搭建分析流程，以实现肽段鉴定结果的迁移；另一类方法则致力于为漏检肽段补全鉴定信息。本研究提出了一种名为靶向提取的分析方法，可在单次实验中完成前体离子的鉴定。该方法通过整合多数据集来源的肽段参考文库，降低假阳性鉴定的风险，并采用诱饵序列与靶标序列的比值完成主流的假发现率（false discovery rate, FDR）质控。类似MSFragger这类工具，将为蛋白质定量相关的蛋白质组学研究工具箱提供极具价值的补充。