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Computational Optimization of Spectral Library Size Improves DIA-MS Proteome Coverage and Applications to 15 Tumors

ABSTRACT: a computational strategy for the size optimization of DIA spectral library, which refines a comprehensive library by a prior analysis of DIA data of a particular tissue type

ORGANISM(S): Homo Sapiens

SUBMITTER: Tiannan Guo

PROVIDER: PXD030648 | iProX | Mon Dec 27 00:00:00 GMT 2021

REPOSITORIES: iProX

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Computational Optimization of Spectral Library Size Improves DIA-MS Proteome Coverage and Applications to 15 Tumors.

Ge Weigang W Liang Xiao X Zhang Fangfei F Hu Yifan Y Xu Luang L Xiang Nan N Sun Rui R Liu Wei W Xue Zhangzhi Z Yi Xiao X Sun Yaoting Y Wang Bo B Zhu Jiang J Lu Cong C Zhan Xiaolu X Chen Lirong L Wu Yan Y Zheng Zhiguo Z Gong Wangang W Wu Qijun Q Yu Jiekai J Ye Zhaoming Z Teng Xiaodong X Huang Shiang S Zheng Shu S Liu Tong T Yuan Chunhui C Guo Tiannan T

Journal of proteome research 20211108 12

Efficient peptide and protein identifications from data-independent acquisition mass spectrometric (DIA-MS) data typically rely on a project-specific spectral library with a suitable size. Here, we describe subLib, a computational strategy for optimizing the spectral library for a specific DIA data set based on a comprehensive spectral library, requiring the preliminary analysis of the DIA data set. Compared with the pan-human library strategy, subLib achieved a 41.2% increase in peptide precurs ...[more]

PMID: 34748352

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