Less label, more free: Approaches in label-free quantitative mass spectrometry

In this review we examine techniques, software, and statistical analyses used in label-free quantitative proteomics studies for area under the curve and spectral counting approaches. Recent advances in the field are discussed in an order that reflects a logical workflow design. Examples of studies t...

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Bibliographic Details
Published in:	Proteomics (Weinheim) Vol. 11; no. 4; pp. 535 - 553
Main Authors:	Neilson, Karlie A, Ali, Naveid A, Muralidharan, Sridevi, Mirzaei, Mehdi, Mariani, Michael, Assadourian, Gariné, Lee, Albert, van Sluyter, Steven C, Haynes, Paul A
Format:	Journal Article
Language:	English
Published:	Weinheim Wiley-VCH Verlag 01-02-2011 WILEY-VCH Verlag WILEY‐VCH Verlag Wiley-VCH Wiley Subscription Services, Inc
Subjects:	Analytical, structural and metabolic biochemistry Biological and medical sciences Fundamental and applied biological sciences. Psychology Label-free quantitation Mass Spectrometry - methods Miscellaneous NSAF Peptide Mapping - methods Proteins Proteomics Proteomics - methods Quantitative proteomics Shotgun proteomics Spectral counting Technology Quantitative proteomics Technology Spectral counting Proteomics Label-free quantitation Shotgun proteomics Mass spectrometry NSAF Quantitative analysis
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Summary:	In this review we examine techniques, software, and statistical analyses used in label-free quantitative proteomics studies for area under the curve and spectral counting approaches. Recent advances in the field are discussed in an order that reflects a logical workflow design. Examples of studies that follow this design are presented to highlight the requirement for statistical assessment and further experiments to validate results from label-free quantitation. Limitations of label-free approaches are considered, label-free approaches are compared with labelling techniques, and forward-looking applications for label-free quantitative data are presented. We conclude that label-free quantitative proteomics is a reliable, versatile, and cost-effective alternative to labelled quantitation.
Bibliography:	http://dx.doi.org/10.1002/pmic.201000553 istex:69492E3F38F596DE44782D98A6E11413B1A81AEF ark:/67375/WNG-WBKTK2V7-7 ArticleID:PMIC201000553 Macquarie University Australian Research Council ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-3 content type line 23 ObjectType-Review-1 ObjectType-Feature-1
ISSN:	1615-9853 1615-9861 1615-9861
DOI:	10.1002/pmic.201000553