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Orbitrap_SciLib
Reputable Mentor II
Reputable Mentor II
Yoon JY, Yeom J, Lee H, Kim K, Na S, Park K, Paek E, Lee C.
BMC Bioinformatics. 2011 Feb 15;12 Suppl 1:S46.
Protein quantification is an essential step in many proteomics experiments. A number of labeling approaches have been proposed and adopted in mass spectrometry (MS) based relative quantification. The mTRAQ, one of the stable isotope labeling methods, is amine-specific and available in triplex format, so that the sample throughput could be doubled when compared with duplex reagents. METHODS AND RESULTS: Here we propose a novel data analysis algorithm for peptide quantification in triplex mTRAQ experiments. It improved the accuracy of quantification in two features. First, it identified and separated triplex isotopic clusters of a peptide in each full MS scan. We designed a schematic model of triplex overlapping isotopic clusters, and separated triplex isotopic clusters by solving cubic equations, which are deduced from the schematic model. Second, it automatically determined the elution areas of peptides. Some peptides have similar atomic masses and elution times, so their elution areas can have overlaps. Our algorithm successfully identified the overlaps and found accurate elution areas. We validated our algorithm using standard protein mixture experiments. CONCLUSION: We showed that our algorithm was able to accurately quantify peptides in triplex mTRAQ experiments. Its software implementation is compatible with Trans-Proteomic Pipeline (TPP), and thus enables high throughput analysis of proteomics data.

http://www.biomedcentral.com/content/pdf/1471-2105-12-S1-S46.pdf
School of Computer Science and Engineering, Seoul National University, Seoul 151-742, Korea.
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