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  • Title: i-RUBY: a novel software for quantitative analysis of highly accurate shotgun-proteomics liquid chromatography/tandem mass spectrometry data obtained without stable-isotope labeling of proteins.
    Author: Wada K, Ogiwara A, Nagasaka K, Tanaka N, Komatsu Y.
    Journal: Rapid Commun Mass Spectrom; 2011 Apr 15; 25(7):960-8. PubMed ID: 21416533.
    Abstract:
    We developed a novel software named i-RUBY (identification-Related qUantification-Based strategY algorithm for liquid chromatography/tandem mass spectrometry (LC/MS/MS) data) that enables us to perform fully automatic ion current-based spectral feature analysis of highly accurate data obtained by LC/MS/MS. At the 1st step, this software utilizes accurate peptide/protein identification information for peak detection and peak matching among measurements. Then, at the 2nd step, it picks yet unidentified peaks and matches them to the peaks identified at the 1st step by a linear interpolation algorithm. The analysis of human plasma externally spiked with a known amount of yeast alcohol dehydrogenase 1 showed a good linear relationship between the amount of protein spiked and the quantitative values obtained by i-RUBY analysis. Experiment using human plasma digests spiked with a mixture of known amounts of synthetic peptides derived from two yeast proteins, alcohol dehydrogenase 1 and glucose-6-phospate isomerase, showed the expansion by the 2nd step of i-RUBY of the lower quantification limits to 1/10 to 1/1000 of those reached only by identified peaks at the 1st step. Good correlations between the i-RUBY results and the amount of proteins were confirmed by the analysis of real samples, i.e., sera of normal subjects and cancer patients, by comparing quantitative values of acute-phase proteins obtained by i-RUBY analysis of LC/MS/MS data with those obtained by an immunological method using Bio-Plex. These results taken together show that i-RUBY is a useful tool for obtaining dependable quantitative information from highly accurate shotgun-proteomics LC/MS/MS data.
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