Abstract
Quantitative proteomics is a growing field where several experimental techniques such as those based around stable isotope labelling are reaching maturity. These advances require the parallel development of informatics tools to process and analyse the data, especially for high-throughput experiments seeking to quantify large numbers of proteins. We have developed a novel algorithm for the quantitative analysis of stable isotope-based proteomics data at the peptide level. Without prior formal identification of the peptides by MS/MS, the algorithm determines the mass charge ratio m/z and retention time t of stable isotope-labelled peptide pairs and calculates their relative ratios. It supports several non-proprietary XML input formats and requires only minimal parameter tuning and runs fully automated. We have tested its performance on a low complexity peptide sample in an initial study. In comparison to a manual analysis and an automated approach using MSQuant, it performs as well or better and therefore we believe it has utility for groups wishing to perform high-throughput experiments.
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Nilse, L. et al. (2010). SILACAnalyzer - A Tool for Differential Quantitation of Stable Isotope Derived Data. In: Masulli, F., Peterson, L.E., Tagliaferri, R. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2009. Lecture Notes in Computer Science(), vol 6160. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14571-1_4
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DOI: https://doi.org/10.1007/978-3-642-14571-1_4
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