Document Detail


Detecting outlier peptides in quantitative high-throughput mass spectrometry data.
MedLine Citation:
PMID:  22483996     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Quantitative high-throughput mass spectrometry has become an established tool to measure relative gene expression proteome-wide. The output of such an experiment usually consists of a list of expression ratios (fold changes) for several thousand proteins between two conditions. However, we observed that individual peptide fold changes may show a significantly different behavior than other peptides from the same protein and that these differences cannot be explained by imprecise measurements. Such outlier peptides can be the consequence of several technical (misidentifications, misquantifications) or biological (post-translational modifications, differential regulation of isoforms) reasons. We developed a method to detect outlier peptides in mass spectrometry data which is able to delineate imprecise measurements from real outlier peptides with high accuracy when the true difference is as small as 1.4 fold. We applied our method to experimental data and investigated the different technical and biological effects that result in outlier peptides. Our method will assist future research to reduce technical bias and can help to identify genes with differentially regulated protein isoforms in high throughput mass spectrometry data.
Authors:
Florian Erhard; Ralf Zimmer
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-3-29
Journal Detail:
Title:  Journal of proteomics     Volume:  -     ISSN:  1876-7737     ISO Abbreviation:  -     Publication Date:  2012 Mar 
Date Detail:
Created Date:  2012-4-9     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101475056     Medline TA:  J Proteomics     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2012. Published by Elsevier B.V.
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