iDIA-QC: AI-empowered data-independent acquisition mass spectrometry-based quality control
Abstract 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 spect...
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Main Authors: | Huanhuan Gao, Yi Zhu, Dongxue Wang, Zongxiang Nie, He Wang, Guibin Wang, Shuang Liang, Yuting Xie, Yingying Sun, Wenhao Jiang, Zhen Dong, Liqin Qian, Xufei Wang, Mengdi Liang, Min Chen, Houqi Fang, Qiufang Zeng, Jiao Tian, Zeyu Sun, Juan Xue, Shan Li, Chen Chen, Xiang Liu, Xiaolei Lyu, Zhenchang Guo, Yingzi Qi, Ruoyu Wu, Xiaoxian Du, Tingde Tong, Fengchun Kong, Liming Han, Minghui Wang, Yang Zhao, Xinhua Dai, Fuchu He, Tiannan Guo |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
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Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-024-54871-1 |
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