correspondence problem for metabonomics datasets

• Published in: Analytical and bioanalytical chemistry Vol. 394; no. 1; pp. 151 - 162
• Main Authors: Åberg, K. Magnus, Alm, Erik, Torgrip, Ralf J. O
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Berlin/Heidelberg : Springer-Verlag 01-05-2009; Springer-Verlag
• Subjects: Alignment; Analytical Chemistry; Biochemistry; Characterization and Evaluation of Materials; Chemistry; Chemistry and Materials Science; chromatography; Databases, Factual; Error analysis; Food Science; Laboratory Medicine; Mass spectrometry (MS); Mathematical analysis; Metabolites; metabolomics; Metabolomics - methods; Monitoring/Environmental Analysis; NMR; Review; Samples; State of the art; Statistical analysis; Statistical methods; Tables (data); Warping; Metabolic profiling; Alignment; NMR; Warping; Chromatography; Mass spectrometry (MS)
• ISSN: 1618-2642; 1618-2650
• DOI: 10.1007/s00216-009-2628-9

In metabonomics it is difficult to tell which peak is which in datasets with many samples. This is known as the correspondence problem. Data from different samples are not synchronised, i.e., the peak from one metabolite does not appear in exactly the same place in all samples. For datasets with many samples, this problem is nontrivial, because each sample contains hundreds to thousands of peaks that shift and are identified ambiguously. Statistical analysis of the data assumes that peaks from one metabolite are found in one column of a data table. For every error in the data table, the statistical analysis loses power and the risk of missing a biomarker increases. It is therefore important to solve the correspondence problem by synchronising samples and there is no method that solves it once and for all. In this review, we analyse the correspondence problem, discuss current state-of-the-art methods for synchronising samples, and predict the properties of future methods.