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Bioinformatics Advance Access originally published online on January 28, 2009
Bioinformatics 2009 25(6):808-814; doi:10.1093/bioinformatics/btp060
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© The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

A novel comprehensive wave-form MS data processing method

Shuo Chen 1,2,3,{dagger}, Ming Li 1,2,{dagger}, Don Hong 4, Dean Billheimer 5, Huiming Li 2, Baogang J. Xu 6 and Yu Shyr 1,2,*

1Division of Cancer Biostatistics, Department of Biostatistics, Vanderbilt University, 2Cancer Biostatistics Center, Vanderbilt-Ingram Cancer Center, Nashville, TN 37232, 3Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, 4Department of Mathematical Sciences, Middle Tennessee State University, Murfreesboro, TN 37132, 5Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112 and 6Department of Cancer Biology, Vanderbilt University, Nashville, TN 37232, USA

*To whom correspondence should be addressed.


  Abstract

Motivation: Mass spectrometry (MS) can generate high-throughput protein profiles for biomedical research to discover biologically related protein patterns/biomarkers. The noisy functional MS data collected by current technologies, however, require consistent, sensitive and robust data-processing techniques for successful biomedical application. Therefore, it is important to detect features precisely for each spectrum, quantify them well and assign a unique label to features from the same protein/peptide across spectra.

Results: In this article, we propose a new comprehensive MS data preprocessing package, Wave-spec, which includes several novel algorithms. It can overcome several conventional difficulties. Wave-spec can be applied to multiple types of MS data generated with different MS technologies. Results from this new package were evaluated and compared to several existing approaches based on a MALDI-TOF MS dataset.

Availability: An example of MATLAB scripts used to implement the methods described in this article, along with Supplementary Figures, can be found at http://www.vicc.org/biostatistics/supp.php.

Contact: yu.shyr{at}vanderbilt.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

{dagger}The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.

Associate Editor: Jonathan Wren

Received on October 2, 2008; revised on January 22, 2009; accepted on January 23, 2009

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