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Bioinformatics Advance Access published online on November 5, 2009
Bioinformatics, doi:10.1093/bioinformatics/btp610
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© The Author (2009). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Methods for combining peptide intensities to estimate relative protein abundance

Brian Carrillo 1, Corey Yanofsky 1, Sylvie Laboissiere 2, Robert Nadon 2,3 and Robert E. Kearney 1,*

1 Department of Biomedical Engineering, McGill University, Montreal, Canada
2 McGill University and Genome Quebec Innovation Centre Proteomics Platform, Montreal, Canada
3 Department of Human Genetics, McGill University, Montreal, Canada

*To whom correspondence should be addressed. Robert E. Kearney


  Abstract

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.

Associate Editor: Prof. Burkhard Rost

Received on September 17, 2009; revised on October 15, 2009; accepted on October 19, 2009

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