Model-based peak alignment of metabolomic profiling from comprehensive two-dimensional gas chromatography mass spectrometry

BMC Bioinformatics

Research Article

Seongho Kim¹  Changyu Shen²  Jaesik Jeong²  Xiang Zhang³  Xue Shi³ 

[1] Department of Bioinformatics and Biostatistics, University of Louisville, 485 E. Gray St, 40292, Louisville, KY, USA;Department of Biostatistics, Indiana University, 410 West 10th Street, 46202, Indianapolis, IN, USA;Department of Chemistry, University of Louisville, 2320 South Brook Street, 40292, Louisville, KY, USA;

关键词: Homogeneous Data;    Peak Pair;    Rank Distance;    Peak Match;    Peak Alignment;   

DOI  :  10.1186/1471-2105-13-27

 received in 2011-10-03, accepted in 2012-02-08,  发布年份 2012

来源: Springer

【 摘 要 】

BackgroundComprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GCxGC/TOF-MS) has been used for metabolite profiling in metabolomics. However, there is still much experimental variation to be controlled including both within-experiment and between-experiment variation. For efficient analysis, an ideal peak alignment method to deal with such variations is in great need.ResultsUsing experimental data of a mixture of metabolite standards, we demonstrated that our method has better performance than other existing method which is not model-based. We then applied our method to the data generated from the plasma of a rat, which also demonstrates good performance of our model.ConclusionsWe developed a model-based peak alignment method to process both homogeneous and heterogeneous experimental data. The unique feature of our method is the only model-based peak alignment method coupled with metabolite identification in an unified framework. Through the comparison with other existing method, we demonstrated that our method has better performance. Data are available at http://stage.louisville.edu/faculty/x0zhan17/software/software-development/mspa. The R source codes are available at http://www.biostat.iupui.edu/~ChangyuShen/CodesPeakAlignment.zip.Trial Registration2136949528613691

【 授权许可】

Unknown   
© Jeong et al; licensee BioMed Central Ltd. 2012. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.