首页|Dear-DIAXMBD:Deep Autoencoder Enables Deconvolution of Data-independent Acquisition Proteomics

Dear-DIAXMBD:Deep Autoencoder Enables Deconvolution of Data-independent Acquisition Proteomics

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Data-independent acquisition(DIA)technology for protein identification from mass spectrometry and related algorithms is developing rapidly.The spectrum-centric analysis of DIA data without the use of spectra library from data-dependent acquisition data represents a promising direction.In this paper,we proposed an untargeted analysis method,Dear-DIAXMBD,for direct analysis of DIA data.Dear-DIAXMBD first integrates the deep variational autoencoder and triplet loss to learn the representations of the extracted fragment ion chromatograms,then uses the k-means clustering algorithm to aggregate fragments with similar representations into the same classes,and finally establishes the inverted index tables to determine the precursors of fragment clusters between precursors and peptides and between fragments and peptides.We show that Dear-DIAXMBD performs superiorly with the highly complicated DIA data of different species obtained by different instrument platforms.Dear-DIAXMBD is publicly available at https://github.com/jianweishuai/Dear-DIA-XMBD.

Qingzu He、Chuan-Qi Zhong、Xiang Li、Huan Guo、Yiming Li、Mingxuan Gao、Rongshan Yu、Xianming Liu、Fangfei Zhang、Donghui Guo、Fangfu Ye、Tiannan Guo、Jianwei Shuai、Jiahuai Han

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Department of Physics,and Fujian Provincial Key Laboratory for Soft Functional Materials Research,Xiamen University,Xiamen 361005,China

Oujiang Laboratory(Zhejiang Lab for Regenerative Medicine,Vision and Brain Health)and Wenzhou Institute,University of Chinese Academy of Sciences,Wenzhou,Zhejiang 325001,China

School of Life Sciences,Xiamen University,Xiamen 361102,China

State Key Laboratory of Cellular Stress Biology,Innovation Center for Cell Signaling Network,Xiamen 361102,China

Department of Computer Science,Xiamen University,Xiamen 361005,China

National Institute for Data Science in Health and Medicine,School of Medicine,Xiamen University,Xiamen 361102,China

Bruker(Beijing)Scientific Technology Co.Ltd.,Beijing,China

Westlake Laboratory of Life Sciences and Biomedicine,Key Laboratory of Structural Biology of Zhejiang Province,School of Life Sciences,Westlake University,18 Shilongshan Road,Hangzhou 310024,China

Institute of Basic Medical Sciences,Westlake Institute for Advanced Study,18 Shilongshan Road,Hangzhou 310024,China

Department of Electronic Engineering,Xiamen University,Xiamen 361005,China

Westlake Omics Ltd.,Yunmeng Road 1,Hangzhou,China

National Institute for Data Science in Health and Medicine,School of Medicine,Xiamen Un

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科技部项目国家自然科学基金国家自然科学基金国家自然科学基金国家自然科学基金中央高校基本科研业务费专项中央高校基本科研业务费专项

STI2030-Major Projects 2021ZD0201900120900528178810111704318J13100272072023001720720190087

2024

10.34133/research.0179

研究(英文)

研究(英文)

CSTPCD
ISSN：
年,卷(期)：2024.2024(1)
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