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Bioinformatics Advance Access originally published online on March 18, 2008
Bioinformatics 2008 24(8):1070-1077; doi:10.1093/bioinformatics/btn078
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© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

A noise model for mass spectrometry based proteomics

Peicheng Du 1,*, Gustavo Stolovitzky 1, Peter Horvatovich 2, Rainer Bischoff 2, Jihyeon Lim 3 and Frank Suits 1

1IBM Computational Biology Center, P.O. Box 218, Yorktown Heights, NY 10598, USA, 2University of Groningen, Antonius Deusinglaan 1, Postbus 196, 9700 AD Groningen, The Netherlands and 3Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA

*To whom correspondence should be addressed.


  Abstract

Motivation: Mass spectrometry data are subjected to considerable noise. Good noise models are required for proper detection and quantification of peptides. We have characterized noise in both quadrupole time-of-flight (Q-TOF) and ion trap data, and have constructed models for the noise.

Results: We find that the noise in Q-TOF data from Applied Biosystems QSTAR fits well to a combination of multinomial and Poisson model with detector dead-time correction. In comparison, ion trap noise from Agilent MSD-Trap-SL is larger than the Q-TOF noise and is proportional to Poisson noise. We then demonstrate that the noise model can be used to improve deisotoping for peptide detection, by estimating appropriate cutoffs of the goodness of fit parameter at prescribed error rates. The noise models also have implications in noise reduction, retention time alignment and significance testing for biomarker discovery.

Contact: pdu{at}us.ibm.com

Supplementary information: Supplementary data are available at Bioinfomatics Online.

Associate Editor: Olga Troyanskaya

Received on September 10, 2007; revised on February 21, 2008; accepted on February 27, 2008

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