Clustering millions of tandem mass spectra.
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 http://peptide.ucsd.edu or can be run online at http://proteomics.bioprojects.org/MassSpec.
Frank
Ari M
AM
Department of Computer Science and Engineering, University of California, San Diego, La Jolla, California 92093-0404, USA. arf@cs.ucsd.edu
Bandeira
Nuno
N
Shen
Zhouxin
Z
Tanner
Stephen
S
Briggs
Steven P
SP
Smith
Richard D
RD
Pevzner
Pavel A
PA
D000595:Amino Acid Sequence; D016000:Cluster Analysis; D019295:Computational Biology; D008969:Molecular Sequence Data; D010455:Peptides / Q000032:analysis*; D040901:Proteomics / Q000379:methods*; D053719:Tandem Mass Spectrometry
D010455:Peptides