Document Detail


A comparative analysis of computational approaches to relative protein quantification using peptide peak intensities in label-free LC-MS proteomics experiments.
MedLine Citation:
PMID:  23019139     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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.
Authors:
Melissa M Matzke; Joseph N Brown; Marina A Gritsenko; Thomas O Metz; Joel G Pounds; Karin D Rodland; Anil K Shukla; Richard D Smith; Katrina M Waters; Jason E McDermott; Bobbie-Jo Webb-Robertson
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Publication Detail:
Type:  Comparative Study; Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, U.S. Gov't, P.H.S.; Review     Date:  2012-11-08
Journal Detail:
Title:  Proteomics     Volume:  13     ISSN:  1615-9861     ISO Abbreviation:  Proteomics     Publication Date:  2013 Feb 
Date Detail:
Created Date:  2013-02-18     Completed Date:  2013-07-31     Revised Date:  2014-02-04    
Medline Journal Info:
Nlm Unique ID:  101092707     Medline TA:  Proteomics     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  493-503     Citation Subset:  IM    
Copyright Information:
© 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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MeSH Terms
Descriptor/Qualifier:
Chromatography, Liquid
Data Interpretation, Statistical
Humans
Linear Models
Mass Spectrometry / methods
Proteome / chemistry,  isolation & purification,  metabolism*
Proteomics
Software
Grant Support
ID/Acronym/Agency:
(8 P41 GM103493-10/GM/NIGMS NIH HHS; 5P41RR018522-10/RR/NCRR NIH HHS; DK071283/DK/NIDDK NIH HHS; P41 GM103493/GM/NIGMS NIH HHS; R33 DK071283/DK/NIDDK NIH HHS; U54 ES016015/ES/NIEHS NIH HHS; U54-016015//PHS HHS
Chemical
Reg. No./Substance:
0/Proteome
Comments/Corrections

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