Title: Improved peak detection and quantification of mass spectrometry data acquired from surface-enhanced laser desorption and ionization by denoising spectra with the undecimated discrete wavelet transform
Abstract: PROTEOMICSVolume 5, Issue 16 p. 4107-4117 Regular Article Improved peak detection and quantification of mass spectrometry data acquired from surface-enhanced laser desorption and ionization by denoising spectra with the undecimated discrete wavelet transform Kevin R. Coombes Dr., Corresponding Author Kevin R. Coombes Dr. [email protected] Department of Biostatistics and Applied Mathematics, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USADepartment of Biostatistics and Applied Mathematics, Box 447, The University of Texas M. D. Anderson Cancer Center, 1500 Holcombe Blvd., Houston, TX 77030, USA Fax: +1-713-745-4949===Search for more papers by this authorSpiridon Tsavachidis, Spiridon Tsavachidis Department of Biostatistics and Applied Mathematics, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USASearch for more papers by this authorJeffrey S. Morris, Jeffrey S. Morris Department of Biostatistics and Applied Mathematics, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USASearch for more papers by this authorKeith A. Baggerly, Keith A. Baggerly Department of Biostatistics and Applied Mathematics, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USASearch for more papers by this authorMien-Chie Hung, Mien-Chie Hung Department of Molecular and Cellular Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, TX , USASearch for more papers by this authorHenry M. Kuerer, Corresponding Author Henry M. Kuerer Department of Surgical Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USADepartment of Biostatistics and Applied Mathematics, Box 447, The University of Texas M. D. Anderson Cancer Center, 1500 Holcombe Blvd., Houston, TX 77030, USA Fax: +1-713-745-4949===Search for more papers by this author Kevin R. Coombes Dr., Corresponding Author Kevin R. Coombes Dr. [email protected] Department of Biostatistics and Applied Mathematics, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USADepartment of Biostatistics and Applied Mathematics, Box 447, The University of Texas M. D. Anderson Cancer Center, 1500 Holcombe Blvd., Houston, TX 77030, USA Fax: +1-713-745-4949===Search for more papers by this authorSpiridon Tsavachidis, Spiridon Tsavachidis Department of Biostatistics and Applied Mathematics, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USASearch for more papers by this authorJeffrey S. Morris, Jeffrey S. Morris Department of Biostatistics and Applied Mathematics, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USASearch for more papers by this authorKeith A. Baggerly, Keith A. Baggerly Department of Biostatistics and Applied Mathematics, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USASearch for more papers by this authorMien-Chie Hung, Mien-Chie Hung Department of Molecular and Cellular Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, TX , USASearch for more papers by this authorHenry M. Kuerer, Corresponding Author Henry M. Kuerer Department of Surgical Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USADepartment of Biostatistics and Applied Mathematics, Box 447, The University of Texas M. D. Anderson Cancer Center, 1500 Holcombe Blvd., Houston, TX 77030, USA Fax: +1-713-745-4949===Search for more papers by this author First published: 27 October 2005 https://doi.org/10.1002/pmic.200401261Citations: 212AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract Mass spectrometry is being used to find disease-related patterns in mixtures of proteins derived from biological fluids. Questions have been raised about the reproducibility and reliability of peak quantifications using this technology. We collected nipple aspirate fluid from breast cancer patients and healthy women, pooled them into a quality control sample, and produced 24 replicate SELDI spectra. We developed a novel algorithm to process the spectra, denoising with the undecimated discrete wavelet transform (UDWT), and evaluated it for consistency and reproducibility. UDWT efficiently decomposes spectra into noise and signal. The noise is consistent and uncorrelated. Baseline correction produces isolated peak clusters separated by flat regions. Our method reproducibly detects more peaks than the method implemented in Ciphergen software. After normalization and log transformation, the mean coefficient of variation of peak heights is 10.6%. Our method to process spectra provides improvements over existing methods. Denoising using the UDWT appears to be an important step toward obtaining results that are more accurate. It improves the reproducibility of quantifications and supplies tools for investigation of the variations in the technology more carefully. Further study will be required, because we do not have a gold standard providing an objective assessment of which peaks are present in the samples. Citing Literature Volume5, Issue16No. 16 November 2005Pages 4107-4117 RelatedInformation
Publication Year: 2005
Publication Date: 2005-11-01
Language: en
Type: article
Indexed In: ['crossref', 'pubmed']
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Cited By Count: 323
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