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Briefings in Bioinformatics Advance Access published online on September 28, 2007
Briefings in Bioinformatics, doi:10.1093/bib/bbm046
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© The Author 2007. Published by Oxford University Press. For Permissions, please email: journals.permissions@oxfordjournals.org

Computational methods for the comparative quantification of proteins in label-free LCn-MS experiments

Jason W. H. Wong, Matthew J. Sullivan and Gerard Cagney

Corresponding author. Jason W. H. Wong, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland. Tel: +35317166945; Fax: +35317166962; E-mail: jason.wong{at}ucd.ie

Liquid chromatography (LC) coupled to electrospray mass spectrometry (MS) is well established in high-throughput proteomics. The technology enables rapid identification of large numbers of proteins in a relatively short time. Comparative quantification of identified proteins from different samples is often regarded as the next step in proteomics experiments enabling the comparison of protein expression in different proteomes. Differential labeling of samples using stable isotope incorporation or conjugation is commonly used to compare protein levels between samples but these procedures are difficult to carry out in the laboratory and for large numbers of samples. Recently, comparative quantification of label-free LCn-MS proteomics data has emerged as an alternative approach. In this review, we discuss different computational approaches for extracting comparative quantitative information from label-free LCn-MS proteomics data. The procedure for computationally recovering the quantitative information is described. Furthermore, statistical tests used to evaluate the relevance of results will also be discussed.

Keywords: comparative quantification, mass spectrometry-based proteomics, label-free quantification, spectral counting, ion chromatogram extraction

Submitted: June 28, 2007. Accepted: September 7, 2007.


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