A Correlation Algorithm for the Automated Quantitative Analysis of Shotgun Proteomics Data

Michael J. MacCoss, Christine C. Wu, Hongbin Liu, Rovshan Sadygov, John R. Yates

Research output: Contribution to journalArticle

233 Scopus citations


Quantitative shotgun proteomic analyses are facilitated using chemical tags such as ICAT and metabolic labeling strategies with stable isotopes. The rapid high-throughput production of quantitative "shotgun" proteomic data necessitates the development of software to automatically convert mass spectrometry-derived data of peptides into relative protein abundances. We describe a computer program called RelEx, which uses a least-squares regression for the calculation of the peptide ion current ratios from the mass spectrometry-derived ion chromatograms. RelEx is tolerant of poor signal-to-noise data and can automatically discard nonusable chromatograms and outlier ratios. We apply a simple correction for systematic errors that improves the accuracy of the quantitative measurement by 32 ± 4%. Our automated approach was validated using labeled mixtures composed of known molar ratios and demonstrated in a real sample by measuring the effect of osmotic stress on protein expression in Saccharomyces cerevisiae.

Original languageEnglish (US)
Pages (from-to)6912-6921
Number of pages10
JournalAnalytical Chemistry
Issue number24
StatePublished - Dec 15 2003
Externally publishedYes


ASJC Scopus subject areas

  • Analytical Chemistry

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