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Bioinformatics Advance Access published online on May 6, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti482
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org
Received March 13, 2005
Revised April 15, 2005
Accepted May 1, 2005

Article

Algorithms for alignment of mass spectrometry proteomic data

Neal Jeffries 1*

1 National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892

* To whom correspondence should be addressed.
Neal Jeffries, E-mail: neal.jeffries{at}nih.gov


  Abstract

Motivation: The analysis of biological samples with high-throughput mass spectrometers has increased greatly in recent years. As larger datasets are processed it is important that the spectra are aligned to ensure that the same protein intensities are correctly identified in each sample. Without such an alignment procedure it is possible to make errors in identifying the signals from peptides with similar molecular weight. Two algorithms are provided that can improve the alignment among samples. One algorithm is designed to work with SELDI data produced from a Ciphergen instrument while the other may be used with data in a more general format.

Results: The two algorithms were applied to samples drawn from a common pool of reference serum. The results indicate substantial improvement in consistently identifying peptide signals in different samples.

Availability: The two algorithms are programmed using the R language and are available from http://krisa.ninds.nih.gov/alignment/.


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