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Assigning significance in label-free quantitative proteomics to include single-peptide-hit proteins with low replicates

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Title: Assigning significance in label-free quantitative proteomics to include single-peptide-hit proteins with low replicates
Author(s): Li, Qingbo
Subject(s): proteins proteomics
Abstract: Selecting differentially regulated proteins with an assignment of statistical significance remains difficult for proteins with a single-peptide hit or a small fold-change when sample replicates are limited. This study presents a label-free quantitative proteomics scheme that was used to select differentially regulated proteins with single-peptide hits and with <2-fold change at a 5% false discovery rate. The scheme incorporated a labeled internal control into two unlabeled samples to facilitate error modeling when there were no replicates for the unlabeled samples. The results showed that, while both a power law global error model with a signal-to-noise ratio statistic (PLGEM-STN) and a constant fold-change threshold could be used, neither of them alone was stringent enough to select differentially regulated proteins at a 5% false discovery rate. Thus, the rule of minimum number of permuted significant pairings (MPSP) was introduced to reduce false discovery rates in combination with PLGEM-STN or a fold-change threshold. MPSP played a critical role in extending the selection of differentially regulated proteins to those with single-peptide hits or with lower fold-changes. Although the approaches were demonstrated for limited sample replicates, they should also be applicable to the situation where more sample replicates are available.
Issue Date: 2010-01-01
Publisher: Hindawi Publishing Corporation
Citation Info: Li, Q. 2010. Assigning significance in label-free quantitative proteomics to include single-peptide-hit proteins with low replicates. International Journal of Proteomics, 2010. DOI: 10.1155/2010/731582
Type: Article
Description: The original source is available through Hindawi Publishing Corporation at DOI: 10.1155/2010/731582. Copyright © 2010 Qingbo Li. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
URI: http://hdl.handle.net/10027/7701
ISSN: 2090-2174
Sponsor: Part of this work was supported by the NIH grant R03AI073469-01A1.
Date Available in INDIGO: 2011-05-27
 

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