title: PepC: proteomics software for identifying differentially expressed proteins based on spectral counting.
abstract: 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.
  
  
  METHODS
  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.
authors.affiliation: Insilicos LLC, Seattle, WA 98109, USA.
authors.forename: N L
authors.initials: NL
authors.lastname: Heinecke
authors.forename: B S
authors.initials: BS
authors.lastname: Pratt
authors.forename: T
authors.initials: T
authors.lastname: Vaisar
authors.forename: L
authors.initials: L
authors.lastname: Becker
mesh_terms: D030562:Databases, Protein; D013058:Mass Spectrometry; D011506:Proteins / Q000737:chemistry*; D020543:Proteome / Q000032:analysis*; D040901:Proteomics / Q000379:methods*; D012984:Software; D014584:User-Computer Interface
chemical_list: D011506:Proteins; D020543:Proteome