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Computational and Mathematical Methods in Medicine
Volume 2013 (2013), Article ID 509761, 12 pages
Research Article

Comparative Analysis of Mass Spectral Similarity Measures on Peak Alignment for Comprehensive Two-Dimensional Gas Chromatography Mass Spectrometry

1Biostatistics Core, Karmanos Cancer Institute, Wayne State University, Detroit, MI 48201, USA
2Department of Chemistry, University of Louisville, Louisville, KY 40292, USA

Received 14 May 2013; Revised 25 July 2013; Accepted 7 August 2013

Academic Editor: Reinoud Maex

Copyright © 2013 Seongho Kim and Xiang Zhang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Peak alignment is a critical procedure in mass spectrometry-based biomarker discovery in metabolomics. One of peak alignment approaches to comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) data is peak matching-based alignment. A key to the peak matching-based alignment is the calculation of mass spectral similarity scores. Various mass spectral similarity measures have been developed mainly for compound identification, but the effect of these spectral similarity measures on the performance of peak matching-based alignment still remains unknown. Therefore, we selected five mass spectral similarity measures, cosine correlation, Pearson’s correlation, Spearman’s correlation, partial correlation, and part correlation, and examined their effects on peak alignment using two sets of experimental GC×GC-MS data. The results show that the spectral similarity measure does not affect the alignment accuracy significantly in analysis of data from less complex samples, while the partial correlation performs much better than other spectral similarity measures when analyzing experimental data acquired from complex biological samples.