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Article: A novel peak detection approach with chemical noise removal using short-time FFT for prOTOF MS data.

TitleA novel peak detection approach with chemical noise removal using short-time FFT for prOTOF MS data.
Authors
Issue Date2009
PublisherWiley - V C H Verlag GmbH & Co KGaA. The Journal's web site is located at http://www.wiley-vch.de/home/proteomics
Citation
Proteomics, 2009, v. 9 n. 15, p. 3833-3842 How to Cite?
AbstractPeak detection is a pivotal first step in biomarker discovery from MS data and can significantly influence the results of downstream data analysis steps. We developed a novel automatic peak detection method for prOTOF MS data, which does not require a priori knowledge of protein masses. Random noise is removed by an undecimated wavelet transform and chemical noise is attenuated by an adaptive short-time discrete Fourier transform. Isotopic peaks corresponding to a single protein are combined by extracting an envelope over them. Depending on the S/N, the desired peaks in each individual spectrum are detected and those with the highest intensity among their peak clusters are recorded. The common peaks among all the spectra are identified by choosing an appropriate cut-off threshold in the complete linkage hierarchical clustering. To remove the 1 Da shifting of the peaks, the peak corresponding to the same protein is determined as the detected peak with the largest number among its neighborhood. We validated this method using a data set of serial peptide and protein calibration standards. Compared with MoverZ program, our new method detects more peaks and significantly enhances S/N of the peak after the chemical noise removal. We then successfully applied this method to a data set from prOTOF MS spectra of albumin and albumin-bound proteins from serum samples of 59 patients with carotid artery disease compared to vascular disease-free patients to detect peaks with S/N> or =2. Our method is easily implemented and is highly effective to define peaks that will be used for disease classification or to highlight potential biomarkers.
Persistent Identifierhttp://hdl.handle.net/10722/75166
ISSN
2015 SCImago Journal Rankings: 1.476
PubMed Central ID
ISI Accession Number ID
Funding AgencyGrant Number
IBIS award (Zhou)
TMHRI scholarship award (Zhou)
Neurology Department, National Naval Medical Center
NIH, Clinical Center
Funding Information:

The opinions expressed herein are those of the authors and do not necessarily reflect the policies of the Department of Health and Human Services, the National Institutes of Health, or the Department of Navy. The authors wish to thank Dr. Lisa Sapp (PerkinElmer) for acquiring all prOTOF MS for clinical samples. This work is partially funded by IBIS award (Zhou) and TMHRI scholarship award (Zhou). This research was supported in part by the Neurology Department, National Naval Medical Center and the Intramural Program of the NIH, Clinical Center. They also thank Dominik Back for proofreading the manuscript.

 

DC FieldValueLanguage
dc.contributor.authorZhang, Sen_HK
dc.contributor.authorDeGraba, TJen_HK
dc.contributor.authorWang, Hen_HK
dc.contributor.authorHoehn, GTen_HK
dc.contributor.authorGonzales, DAen_HK
dc.contributor.authorSuffredini, AFen_HK
dc.contributor.authorChing, WKen_HK
dc.contributor.authorNg, MKen_HK
dc.contributor.authorZhou, Xen_HK
dc.contributor.authorWong, STen_HK
dc.date.accessioned2010-09-06T07:08:34Z-
dc.date.available2010-09-06T07:08:34Z-
dc.date.issued2009en_HK
dc.identifier.citationProteomics, 2009, v. 9 n. 15, p. 3833-3842en_HK
dc.identifier.issn1615-9861en_HK
dc.identifier.urihttp://hdl.handle.net/10722/75166-
dc.description.abstractPeak detection is a pivotal first step in biomarker discovery from MS data and can significantly influence the results of downstream data analysis steps. We developed a novel automatic peak detection method for prOTOF MS data, which does not require a priori knowledge of protein masses. Random noise is removed by an undecimated wavelet transform and chemical noise is attenuated by an adaptive short-time discrete Fourier transform. Isotopic peaks corresponding to a single protein are combined by extracting an envelope over them. Depending on the S/N, the desired peaks in each individual spectrum are detected and those with the highest intensity among their peak clusters are recorded. The common peaks among all the spectra are identified by choosing an appropriate cut-off threshold in the complete linkage hierarchical clustering. To remove the 1 Da shifting of the peaks, the peak corresponding to the same protein is determined as the detected peak with the largest number among its neighborhood. We validated this method using a data set of serial peptide and protein calibration standards. Compared with MoverZ program, our new method detects more peaks and significantly enhances S/N of the peak after the chemical noise removal. We then successfully applied this method to a data set from prOTOF MS spectra of albumin and albumin-bound proteins from serum samples of 59 patients with carotid artery disease compared to vascular disease-free patients to detect peaks with S/N> or =2. Our method is easily implemented and is highly effective to define peaks that will be used for disease classification or to highlight potential biomarkers.en_HK
dc.languageengen_HK
dc.publisherWiley - V C H Verlag GmbH & Co KGaA. The Journal's web site is located at http://www.wiley-vch.de/home/proteomicsen_HK
dc.relation.ispartofProteomicsen_HK
dc.rightsThe definitive version is available at www3.interscience.wiley.com-
dc.subject.meshBlood Proteins - analysis-
dc.subject.meshCarotid Artery Diseases - blood - diagnosis-
dc.subject.meshMass Spectrometry - methods-
dc.subject.meshProteomics - methods-
dc.subject.meshSoftware-
dc.titleA novel peak detection approach with chemical noise removal using short-time FFT for prOTOF MS data.en_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1615-9853&volume=9&issue=15&spage=3833&epage=3842&date=2009&atitle=A+novel+peak+detection+approach+with+chemical+noise+removal+using+short-time+FFT+for+prOTOF+MS+dataen_HK
dc.identifier.emailChing, WK:wching@hku.hken_HK
dc.identifier.authorityChing, WK=rp00679en_HK
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1002/pmic.200800030en_HK
dc.identifier.pmid19681055-
dc.identifier.pmcidPMC2782493-
dc.identifier.scopuseid_2-s2.0-70350437429en_HK
dc.identifier.hkuros168196en_HK
dc.identifier.volume9en_HK
dc.identifier.issue15en_HK
dc.identifier.spage3833en_HK
dc.identifier.epage3842en_HK
dc.identifier.isiWOS:000269408400006-
dc.identifier.scopusauthoridZhang, S=10143093600en_HK
dc.identifier.scopusauthoridDeGraba, TJ=36882780100en_HK
dc.identifier.scopusauthoridWang, H=16644207700en_HK
dc.identifier.scopusauthoridHoehn, GT=6602266523en_HK
dc.identifier.scopusauthoridGonzales, DA=16230320800en_HK
dc.identifier.scopusauthoridSuffredini, AF=7004346468en_HK
dc.identifier.scopusauthoridChing, WK=13310265500en_HK
dc.identifier.scopusauthoridNg, MK=34571761900en_HK
dc.identifier.scopusauthoridZhou, X=8914487400en_HK
dc.identifier.scopusauthoridWong, ST=12781047500en_HK

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