期刊
BMC BIOINFORMATICS
卷 12, 期 -, 页码 -出版社
BMC
DOI: 10.1186/1471-2105-12-74
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资金
- San Antonio Life Sciences Institute Research Enhancement
- National Institute of Health [NIH 2G12RR013646-11]
- Cancer Therapy and Research Center (CTRC) at the University of Texas Health Science Center San Antonio, an NCI-designated Cancer Center [NIH P30CA54174]
- Virginia G. Piper Charitable Trust
- Flinn Foundation of Arizona
Background: Relative isotope abundance quantification, which can be used for peptide identification and differential peptide quantification, plays an important role in liquid chromatography-mass spectrometry (LC-MS)based proteomics. However, several major issues exist in the relative isotopic quantification of peptides on time-of-flight (TOF) instruments: LC peak boundary detection, thermal noise suppression, interference removal and mass drift correction. We propose to use the Maximum Ratio Combining (MRC) method to extract MS signal templates for interference detection/removal and LC peak boundary detection. In our method, MRCQuant, MS templates are extracted directly from experimental values, and the mass drift in each LC-MS run is automatically captured and compensated. We compared the quantification accuracy of MRCQuant to that of another representative LC-MS quantification algorithm (msInspect) using datasets downloaded from a public data repository. Results: MRCQuant showed significant improvement in the number of accurately quantified peptides. Conclusions: MRCQuant effectively addresses major issues in the relative quantification of LC-MS-based proteomics data, and it provides improved performance in the quantification of low abundance peptides.
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