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LFAQ: Toward Unbiased Label-Free Absolute Protein Quantification by Predicting Peptide Quantitative Factors
Chang, Cheng1; Gao, Zhiqiang2,3; Ying, Wantao1; Fu, Yan2,3; Zhao, Yan1; Wu, Songfeng1; Li, Mengjie2,3; Wang, Guibin1; Qian, Xiaohong1; Zhu, Yunping1,4; He, Fuchu1
2019-01-15
发表期刊ANALYTICAL CHEMISTRY
ISSN0003-2700
卷号91期号:2页码:1335-1343
摘要Mass spectrometry (MS) has become a predominant choice for large-scale absolute protein quantification, but its quantification accuracy still has substantial room for improvement. A crucial issue is the bias between the peptide MS intensity and the actual peptide abundance, i.e., the fact that peptides with equal abundance may have different MS intensities. This bias is mainly caused by the diverse physicochemical properties of peptides. Here, we propose an algorithm for label-free absolute protein quantification, LFAQ which can correct the biased MS intensities by using the predicted peptide quantitative factors for all identified peptides. When validated on data sets produced by different MS instruments and data acquisition modes, LFAQ presented accuracy and precision superior to those of existing methods. In particular, it reduced the quantification error by an average of 46% for low-abundance proteins. The advantages of LFAQ were further confirmed using the data from published papers.
DOI10.1021/acs.analchem.8b03267
语种英语
资助项目National Basic Research Program of China[2017YFA0505002] ; National Basic Research Program of China[2017YFC0906600] ; National Basic Research Program of China[2016YFA0501300] ; National Basic Research Program of China[2014CBA02001] ; Strategic Priority Research Program of CAS[XDB13040600] ; National Natural Science Foundation of China[21605159] ; National Natural Science Foundation of China[21475150] ; NCMIS CAS ; [16CXZ027]
WOS研究方向Chemistry
WOS类目Chemistry, Analytical
WOS记录号WOS:000456350000019
出版者AMER CHEMICAL SOC
引用统计
文献类型期刊论文
条目标识符http://ir.amss.ac.cn/handle/2S8OKBNM/32191
专题应用数学研究所
通讯作者Fu, Yan; Qian, Xiaohong; Zhu, Yunping; He, Fuchu
作者单位1.Beijing Inst Lifeom, State Key Lab Prote, Beijing Proteome Res Ctr, Natl Ctr Prot Sci Beijing, Beijing 102206, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, Natl Ctr Math & Interdisciplinary Sci, Key Lab Random Complex Struct & Data Sci, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100049, Peoples R China
4.Anhui Med Univ, Hefei 230032, Anhui, Peoples R China
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Chang, Cheng,Gao, Zhiqiang,Ying, Wantao,et al. LFAQ: Toward Unbiased Label-Free Absolute Protein Quantification by Predicting Peptide Quantitative Factors[J]. ANALYTICAL CHEMISTRY,2019,91(2):1335-1343.
APA Chang, Cheng.,Gao, Zhiqiang.,Ying, Wantao.,Fu, Yan.,Zhao, Yan.,...&He, Fuchu.(2019).LFAQ: Toward Unbiased Label-Free Absolute Protein Quantification by Predicting Peptide Quantitative Factors.ANALYTICAL CHEMISTRY,91(2),1335-1343.
MLA Chang, Cheng,et al."LFAQ: Toward Unbiased Label-Free Absolute Protein Quantification by Predicting Peptide Quantitative Factors".ANALYTICAL CHEMISTRY 91.2(2019):1335-1343.
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