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De Novo Analysis of Peptide Tandem Mass Spectra by Spectral Graph Partitioning
KSPublications
: De Novo Analysis of Peptide Tandem Mass Spectra by Spectral Graph Partitioning
Title
De Novo Analysis of Peptide Tandem Mass Spectra by Spectral Graph Partitioning
Authors
Bern, M. and Goldberg, D.
Abstract
We report on a new de novo peptide sequencing algorithm that uses spectral graph partitioning. In this approach, relationships between m/z peaks are represented by attractive and repulsive springs, and the vibrational modes of the spring system are used to infer information about the peaks (such as “likely b-ion” or “likely y-ion”). We demonstrate the effectiveness of this approach by comparison with other de novo sequencers on test sets of ion-trap and QTOF spectra, including spectra of mixtures of peptides. On all datasets, we outperform the other sequencers. Along with spectral graph theory techniques, the new de novo sequencer EigenMS incorporates another improvement of independent interest: robust statistical methods for recalibration of time-of-flight mass measurements. Robust recalibration greatly outperforms simple least-squares recalibration, achieving about three times the accuracy for one QTOF dataset.
Journal
Journal of Computational Biology
Date
10/26/2006
Link
Reference
Bern, M. and Goldberg, D. (2006) De Novo Analysis of Peptide Tandem Mass Spectra by Spectral Graph Partitioning. Journal of Computational Biology. 13:2, p. 364-378
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Created at 10/26/2007 7:53 AM by Joshua Kunken
Last modified at 10/26/2007 7:53 AM by Joshua Kunken
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