NDLI: Tools for Label-free Peptide Quantification*

Content Provider	PubMed Central
Author	Nahnsen, Sven Chris, Bielow Reinert, Knut Oliver, Kohlbacher
Copyright Year	2013
Abstract	The increasing scale and complexity of quantitative proteomics studies complicate subsequent analysis of the acquired data. Untargeted label-free quantification, based either on feature intensities or on spectral counting, is a method that scales particularly well with respect to the number of samples. It is thus an excellent alternative to labeling techniques. In order to profit from this scalability, however, data analysis has to cope with large amounts of data, process them automatically, and do a thorough statistical analysis in order to achieve reliable results. We review the state of the art with respect to computational tools for label-free quantification in untargeted proteomics. The two fundamental approaches are feature-based quantification, relying on the summed-up mass spectrometric intensity of peptides, and spectral counting, which relies on the number of MS/MS spectra acquired for a certain protein. We review the current algorithmic approaches underlying some widely used software packages and briefly discuss the statistical strategies for analyzing the data.
Related Links	http://dx.doi.org/10.1074/mcp.r112.025163
Ending Page	556
Page Count	8
Starting Page	549
File Format	PDF
ISSN	15359476
e-ISSN	15359484
Journal	Molecular & Cellular Proteomics : MCP
Issue Number	3
Volume Number	12
Language	English
Publisher	The American Society for Biochemistry and Molecular Biology
Publisher Date	2013-03-01
Access Restriction	Open
Rights Holder	The American Society for Biochemistry and Molecular Biology
Subject Keyword	Analytical Chemistry Biochemistry Molecular Biology Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Medicine Analytical Chemistry Molecular Biology Biochemistry

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