PepC: proteomics software for identifying differentially expressed proteins based on spectral counting
Open Access
- 22 April 2010
- journal article
- research article
- Published by Oxford University Press (OUP) in Bioinformatics
- Vol. 26 (12), 1574-1575
- https://doi.org/10.1093/bioinformatics/btq171
Abstract
Summary: Identifying biologically significant changes in protein abundance between two conditions is a key issue when analyzing proteomic data. One widely used approach centers on spectral counting, a label-free method that sums all the tandem mass spectra for a protein observed in an analysis. To assess the significance of the results, we recently combined the t-test and G-test, with random permutation analysis, and we validated this approach biochemically. To automate the statistical method, we developed PepC, a software program that balances the trade-off between the number of differentially expressed proteins identified and the false discovery rate. This tool can be applied to a wide range of proteomic datasets, making data analysis rapid, reproducible and easily interpretable by proteomics specialists and non-specialists alike. Availability and implementation: The software is implemented in Java. It has been added to the Trans Proteomic Pipeline project's ‘Petunia’ web interface, but can also be run as a command line program. The source code is GNU Lesser General Public License and the program is freely available on the web. http://sashimi.svn.sourceforge.net/viewvc/sashimi/trunk/trans_proteomic_pipeline/src/Quantitation/Pepc Contact:levb@u.washington.edu; brian.pratt@insilicos.comKeywords
This publication has 14 references indexed in Scilit:
- A Macrophage Sterol-Responsive Network Linked to AtherogenesisCell Metabolism, 2010
- Spectral Index for Assessment of Differential Protein Expression in Shotgun ProteomicsJournal of Proteome Research, 2008
- Detecting Differential and Correlated Protein Expression in Label-Free Shotgun ProteomicsJournal of Proteome Research, 2006
- Comparison of Label-free Methods for Quantifying Human Proteins by Shotgun ProteomicsMolecular & Cellular Proteomics, 2005
- Differential Mass Spectrometry: A Label-Free LC−MS Method for Finding Significant Differences in Complex Peptide and Protein MixturesAnalytical Chemistry, 2004
- A Model for Random Sampling and Estimation of Relative Protein Abundance in Shotgun ProteomicsAnalytical Chemistry, 2004
- Statistical tests for differential expression in cDNA microarray experimentsGenome Biology, 2003
- Mass spectrometry-based proteomicsNature, 2003
- Quantitative Analysis of Modified Proteins by LC−MS/MS of Peptides Labeled with Phenyl IsocyanateJournal of Proteome Research, 2003
- Identification and Relative Quantitation of Protein Mixtures by Enzymatic Digestion Followed by Capillary Reversed-Phase Liquid Chromatography−Tandem Mass SpectrometryAnalytical Chemistry, 2002