{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T04:18:06Z","timestamp":1773289086236,"version":"3.50.1"},"reference-count":16,"publisher":"Oxford University Press (OUP)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,6,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>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.<\/jats:p><jats:p>Availability and implementation: The software is implemented in Java. It has been added to the Trans Proteomic Pipeline project's \u2018Petunia\u2019 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<\/jats:p><jats:p>Contact: \u00a0levb@u.washington.edu; brian.pratt@insilicos.com<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq171","type":"journal-article","created":{"date-parts":[[2010,4,23]],"date-time":"2010-04-23T02:00:04Z","timestamp":1271988004000},"page":"1574-1575","source":"Crossref","is-referenced-by-count":40,"title":["PepC: proteomics software for identifying differentially expressed proteins based on spectral counting"],"prefix":"10.1093","volume":"26","author":[{"given":"N.L.","family":"Heinecke","sequence":"first","affiliation":[{"name":"1 Insilicos LLC and 2 Department of Medicine, University of Washington, Seattle, WA 98109, USA"}]},{"given":"B.S.","family":"Pratt","sequence":"additional","affiliation":[{"name":"1 Insilicos LLC and 2 Department of Medicine, University of Washington, Seattle, WA 98109, USA"}]},{"given":"T.","family":"Vaisar","sequence":"additional","affiliation":[{"name":"1 Insilicos LLC and 2 Department of Medicine, University of Washington, Seattle, WA 98109, USA"}]},{"given":"L.","family":"Becker","sequence":"additional","affiliation":[{"name":"1 Insilicos LLC and 2 Department of Medicine, University of Washington, Seattle, WA 98109, USA"}]}],"member":"286","published-online":{"date-parts":[[2010,4,22]]},"reference":[{"key":"2023012508054156700_B1","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1038\/nature01511","article-title":"Mass spectrometry-based proteomics","volume":"422","author":"Aebersold","year":"2003","journal-title":"Nature"},{"key":"2023012508054156700_B2","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.cmet.2010.01.003","article-title":"A macrophage sterol-responsive network linked to atherogenesis","volume":"11","author":"Becker","year":"2010","journal-title":"Cell Metab."},{"key":"2023012508054156700_B3","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","article-title":"Controlling the false discovery rate\u2013a practical and powerful approach to multiple testing","volume":"57","author":"Benjamini","year":"1995","journal-title":"J. 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