Spectral dictionaries: Integrating de novo peptide sequencing with database search of tandem mass spectra.
Database search tools identify peptides by matching tandem mass spectra against a protein database. We study an alternative approach when all plausible de novo interpretations of a spectrum (spectral dictionary) are generated and then quickly matched against the database. We present a new MS-Dictionary algorithm for efficiently generating spectral dictionaries and demonstrate that MS-Dictionary can identify spectra that are missed in the database search. We argue that MS-Dictionary enables proteogenomics searches in six-frame translation of genomic sequences that may be prohibitively time-consuming for existing database search approaches. We show that such searches allow one to correct sequencing errors and find programmed frameshifts.
Kim
Sangtae
S
Department of Computer Science and Engineering, University of California San Diego, La Jolla, California 92093, USA.
Gupta
Nitin
N
Bandeira
Nuno
N
Pevzner
Pavel A
PA
D000465:Algorithms; D000595:Amino Acid Sequence; D030562:Databases, Protein; D015894:Genome, Human; D006801:Humans; D008969:Molecular Sequence Data; D010455:Peptides / Q000032:analysis / Q000737:chemistry*; D020539:Sequence Analysis, Protein / Q000379:methods*; D020592:Shewanella / Q000737:chemistry; D053719:Tandem Mass Spectrometry / Q000379:methods*
D010455:Peptides