Detection and correction of interference in SRM analysis
Selected Reaction Monitoring (SRM) is a method of choice for accurate quantitation of low-abundance proteins in complex backgrounds. This strategy is, however, sensitive to interference from other components in the sample that have the same precursor and fragment masses as the monitored transitions....
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| Veröffentlicht in: | Methods (San Diego, Calif.) Calif.), 2013-06, Vol.61 (3), p.299-303 |
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| creator | Bao, Y. Waldemarson, S. Zhang, G. Wahlander, A. Ueberheide, B. Myung, S. Reed, B. Molloy, K. Padovan, J.C. Eriksson, J. Neubert, T.A. Chait, B.T. Fenyö, D. |
| description | Selected Reaction Monitoring (SRM) is a method of choice for accurate quantitation of low-abundance proteins in complex backgrounds. This strategy is, however, sensitive to interference from other components in the sample that have the same precursor and fragment masses as the monitored transitions. We present here an approach to detect interference by using the expected relative intensity of SRM transitions. We also designed an algorithm to automatically detect the linear range of calibration curves. These approaches were applied to the experimental data of Clinical Proteomic Tumor Analysis Consortium (CPTAC) Verification Work Group Study 7 and show that the corrected measurements provide more accurate quantitation than the uncorrected data. |
| doi_str_mv | 10.1016/j.ymeth.2013.05.008 |
| format | Article |
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This strategy is, however, sensitive to interference from other components in the sample that have the same precursor and fragment masses as the monitored transitions. We present here an approach to detect interference by using the expected relative intensity of SRM transitions. We also designed an algorithm to automatically detect the linear range of calibration curves. These approaches were applied to the experimental data of Clinical Proteomic Tumor Analysis Consortium (CPTAC) Verification Work Group Study 7 and show that the corrected measurements provide more accurate quantitation than the uncorrected data.</description><identifier>ISSN: 1046-2023</identifier><identifier>ISSN: 1095-9130</identifier><identifier>EISSN: 1095-9130</identifier><identifier>DOI: 10.1016/j.ymeth.2013.05.008</identifier><identifier>PMID: 23707623</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Algorithms ; Analytical Chemistry ; Analytisk kemi ; Bioinformatics and Systems Biology ; Bioinformatik och systembiologi ; Calibration ; Humans ; Interference correction ; Interference detection ; Linear range detection ; Mass spectrometry ; Peptide Fragments - analysis ; Proteins - analysis ; Proteomics - methods ; Proteomics - statistics & numerical data ; Selected reaction monitoring ; Signal-To-Noise Ratio ; Tandem Mass Spectrometry - standards ; Validation Studies as Topic</subject><ispartof>Methods (San Diego, Calif.), 2013-06, Vol.61 (3), p.299-303</ispartof><rights>2013 The Authors</rights><rights>Copyright © 2013 The Authors. 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| fulltext | fulltext |
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| ispartof | Methods (San Diego, Calif.), 2013-06, Vol.61 (3), p.299-303 |
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| source | MEDLINE; Elsevier ScienceDirect |
| subjects | Algorithms Analytical Chemistry Analytisk kemi Bioinformatics and Systems Biology Bioinformatik och systembiologi Calibration Humans Interference correction Interference detection Linear range detection Mass spectrometry Peptide Fragments - analysis Proteins - analysis Proteomics - methods Proteomics - statistics & numerical data Selected reaction monitoring Signal-To-Noise Ratio Tandem Mass Spectrometry - standards Validation Studies as Topic |
| title | Detection and correction of interference in SRM analysis |
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