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An Alternating Direction Minimization based denoising method for extracted ion chromatogram
Li,Tianjun1; Chen,Long1; Lu,Xiliang2
2020-11
Source PublicationCHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
ISSN0169-7439
Volume206Pages:104138
Abstract

Accurate extracted ion chromatograms (XIC or EIC) is of great importance for Liquid chromatography - mass spectrometry (LC-MS) based quantitative proteomics. However, current preprocessing methods for XIC mainly focus on removing the peaks of low quality. Such operations are helpful for quantitation, but also contain two potential disadvantages: one is that some valuable information may be lost after the peak removal, and the other is that the retained peak lists are still contain noise. Both of the potential disadvantages may bias the final quantitative results. To solve these problems, we proposed an Alternating Direction Minimization (ADM) based denoising framework for XIC. This framework splits the observed XIC signal into baseline (background), noise and true signal, and the true signal is extracted for further analysis. The advantage of this framework is that the inner relationships over each XIC are considered, for which means that the XIC data is handled in a global way. Also, this framework is not sensitive to the noise type, so that it can be applied to wider applications. We adopted the framework for some sample data for quantitation. The quantitative results are employed to show the performance of XIC denoising. Experimental results confirm that the proposed method provides better and more reliable quantitations.

KeywordDenoise Extracted Ion Chromatogram Mass Spectra Noise Reduction Proteomics
DOI10.1016/j.chemolab.2020.104138
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaAutomation & Control Systems ; Chemistry ; Computer Science ; Instruments & Instrumentationmathematics
WOS SubjectAutomation & Control Systems ; Chemistry, Analytical ; Computer Science, Artificial Intelligenceinstruments & Instrumentation ; Mathematics, Interdisciplinary Applications ; Statistics & Probability
WOS IDWOS:000595160800018
PublisherELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
Scopus ID2-s2.0-85090732820
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Citation statistics
Document TypeJournal article
CollectionFaculty of Science and Technology
DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorChen,Long
Affiliation1.Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Taipa, Macau
2.School of Mathematics and Statistics, Wuhan University, Wuhan, Hubei, China
First Author AffilicationFaculty of Science and Technology
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Li,Tianjun,Chen,Long,Lu,Xiliang. An Alternating Direction Minimization based denoising method for extracted ion chromatogram[J]. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2020, 206, 104138.
APA Li,Tianjun., Chen,Long., & Lu,Xiliang (2020). An Alternating Direction Minimization based denoising method for extracted ion chromatogram. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 206, 104138.
MLA Li,Tianjun,et al."An Alternating Direction Minimization based denoising method for extracted ion chromatogram".CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 206(2020):104138.
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