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A comparative analysis of computational approaches to relative protein quantification using peptide peak intensities in label-free LC-MS proteomics experiments.

TitleA comparative analysis of computational approaches to relative protein quantification using peptide peak intensities in label-free LC-MS proteomics experiments.
Publication TypeJournal Article
Year of Publication2013
AuthorsMatzke MM, Brown JN, Gritsenko MA, Metz TO, Pounds JG, Rodland KD, Shukla AK, Smith RD, Waters KM, McDermott JE, Webb-Robertson B-J
JournalProteomics
KeywordsChromatography, Liquid, Data Interpretation, Statistical, Humans, Linear Models, Mass Spectrometry, Proteome, Proteomics, Software
Abstract

Liquid chromatography coupled with mass spectrometry (LC-MS) is widely used to identify and quantify peptides in complex biological samples. In particular, label-free shotgun proteomics is highly effective for the identification of peptides and subsequently obtaining a global protein profile of a sample. As a result, this approach is widely used for discovery studies. Typically, the objective of these discovery studies is to identify proteins that are affected by some condition of interest (e.g. disease, exposure). However, for complex biological samples, label-free LC-MS proteomics experiments measure peptides and do not directly yield protein quantities. Thus, protein quantification must be inferred from one or more measured peptides. In recent years, many computational approaches to relative protein quantification of label-free LC-MS data have been published. In this review, we examine the most commonly employed quantification approaches to relative protein abundance from peak intensity values, evaluate their individual merits, and discuss challenges in the use of the various computational approaches.

DOI10.1002/pmic.201200269
Alternate JournalProteomics
PubMed ID23019139
PubMed Central IDPMC3775642
Grant List(8 P41 GM103493-10 / GM / NIGMS NIH HHS / United States
5P41RR018522-10 / RR / NCRR NIH HHS / United States
DK071283 / DK / NIDDK NIH HHS / United States
P41 GM103493 / GM / NIGMS NIH HHS / United States
R33 DK071283 / DK / NIDDK NIH HHS / United States
U54 ES016015 / ES / NIEHS NIH HHS / United States
U54-016015 / / PHS HHS / United States
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