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J Proteome Res. 2008 Jan;7(1):113-22. Epub 2007 Dec 8.

Clustering millions of tandem mass spectra.

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Department of Computer Science and Engineering, University of California, San Diego, La Jolla, California 92093-0404, USA.


Tandem mass spectrometry (MS/MS) experiments often generate redundant data sets containing multiple spectra of the same peptides. Clustering of MS/MS spectra takes advantage of this redundancy by identifying multiple spectra of the same peptide and replacing them with a single representative spectrum. Analyzing only representative spectra results in significant speed-up of MS/MS database searches. We present an efficient clustering approach for analyzing large MS/MS data sets (over 10 million spectra) with a capability to reduce the number of spectra submitted to further analysis by an order of magnitude. The MS/MS database search of clustered spectra results in fewer spurious hits to the database and increases number of peptide identifications as compared to regular nonclustered searches. Our open source software MS-Clustering is available for download at or can be run online at

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