文献类型： 外文期刊
第一作者： Gao, Huanhuan
作者： Gao, Huanhuan;Zhu, Yi;Wang, He;Xie, Yuting;Sun, Yingying;Jiang, Wenhao;Dong, Zhen;Qian, Liqin;Guo, Tiannan;Gao, Huanhuan;Zhu, Yi;Wang, He;Xie, Yuting;Sun, Yingying;Jiang, Wenhao;Dong, Zhen;Qian, Liqin;Guo, Tiannan;Gao, Huanhuan;Zhu, Yi;Wang, He;Xie, Yuting;Sun, Yingying;Jiang, Wenhao;Dong, Zhen;Qian, Liqin;Guo, Tiannan;Wang, Dongxue;Wang, Guibin;He, Fuchu;Wang, Dongxue;He, Fuchu;Nie, Zongxiang;Liang, Shuang;Wang, Xufei;Liang, Mengdi;Chen, Min;Fang, Houqi;Zeng, Qiufang;Tian, Jiao;Sun, Zeyu;Xue, Juan;Li, Shan;Xue, Juan;Li, Shan;Chen, Chen;Liu, Xiang;Lyu, Xiaolei;Kong, Fengchun;Guo, Zhenchang;Qi, Yingzi;Tong, Tingde;Wu, Ruoyu;Du, Xiaoxian;Han, Liming;Wang, Minghui;Zhao, Yang;Dai, Xinhua
作者机构：
期刊名称：NATURE COMMUNICATIONS （ 影响因子：15.7； 五年影响因子：17.2 ）
ISSN：
年卷期： 2025 年 16 卷 1 期
页码：
收录情况： SCI
摘要： Quality control (QC) in mass spectrometry (MS)-based proteomics is mainly based on data-dependent acquisition (DDA) analysis of standard samples. Here, we collect 2754 files acquired by data independent acquisition (DIA) and paired 2638 DDA files from mouse liver digests using 21 mass spectrometers across nine laboratories over 31 months. Our data demonstrate that DIA-based LC-MS/MS-related consensus QC metrics exhibit higher sensitivity compared to DDA-based QC metrics in detecting changes in LC-MS status. We then prioritize 15 metrics and invite 21 experts to manually assess the quality of 2754 DIA files based on those metrics. We develop an AI model for DIA-based QC using 2110 training files. It achieves AUCs of 0.91 (LC) and 0.97 (MS) in the first validation dataset (n = 528), and 0.78 (LC) and 0.94 (MS) in an independent validation dataset (n = 116). Finally, we develop an offline software called iDIA-QC for convenient adoption of this methodology.
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