Journal Article

Methods for combining peptide intensities to estimate relative protein abundance

Brian Carrillo, Corey Yanofsky, Sylvie Laboissiere, Robert Nadon and Robert E. Kearney

in Bioinformatics

Volume 26, issue 1, pages 98-103
Published in print January 2010 | ISSN: 1367-4803
Published online November 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp610
Methods for combining peptide intensities to estimate relative protein abundance

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Motivation: Labeling techniques are being used increasingly to estimate relative protein abundances in quantitative proteomic studies. These techniques require the accurate measurement of correspondingly labeled peptide peak intensities to produce high-quality estimates of differential expression ratios. In mass spectrometers with counting detectors, the measurement noise varies with intensity and consequently accuracy increases with the number of ions detected. Consequently, the relative variability of peptide intensity measurements varies with intensity. This effect must be accounted for when combining information from multiple peptides to estimate relative protein abundance.

Results: We examined a variety of algorithms that estimate protein differential expression ratios from multiple peptide intensity measurements. Algorithms that account for the variation of measurement error with intensity were found to provide the most accurate estimates of differential abundance. A simple Sum-of-Intensities algorithm provided the best estimates of true protein ratios of all algorithms tested.

Contact: robert.kearney@mcgill.ca

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  3933 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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