LFAQ: Toward Unbiased Label-Free Absolute Protein Quantification by Predicting Peptide Quantitative Factors

doi:10.1021/acs.analchem.8b03267

CSpace > 应用数学研究所

	LFAQ: Toward Unbiased Label-Free Absolute Protein Quantification by Predicting Peptide Quantitative Factors
	Chang, Cheng 1; Gao, Zhiqiang 2,3; Ying, Wantao 1; Fu, Yan2,3 ; Zhao, Yan 1; Wu, Songfeng 1; Li, Mengjie 2,3; Wang, Guibin 1; Qian, Xiaohong 1; Zhu, Yunping 1,4; He, Fuchu 1
	2019-01-15
Source Publication	ANALYTICAL CHEMISTRY
ISSN	0003-2700
Volume	91 Issue:2 Pages:1335-1343
Abstract	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.
DOI	10.1021/acs.analchem.8b03267
Language	英语
Funding Project	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 Research Area	Chemistry
WOS Subject	Chemistry, Analytical
WOS ID	WOS:000456350000019
Publisher	AMER CHEMICAL SOC
Citation statistics
Document Type	期刊论文
Identifier	http://ir.amss.ac.cn/handle/2S8OKBNM/32191
Collection	应用数学研究所
Corresponding Author	Fu, Yan; Qian, Xiaohong; Zhu, Yunping; He, Fuchu
Affiliation	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
Recommended Citation GB/T 7714	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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