An automated method for peak detection and matching in large gas chromatography-mass spectrometry data sets

Journal of Chemometrics

Volumn 20, Issue 8-10, 2006, Pages 325-340

  Dixon, Sarah J ^a   Brereton, Richard G ^a   Soini, Helena A ^b   Novotny, Milos V ^b   Penn, Dustin J ^c  

^a UNIVERSITY OF BRISTOL   (United Kingdom)

^b INDIANA UNIVERSITY   (United States)

^c KONRAD LORENZ INSTITUTE FOR ETHOLOGY   (Austria)

Author keywords

GC MS; Metabolomics; Peak detection; Peak matching

Indexed keywords

CHROMATOGRAPHIC ANALYSIS; DATA HANDLING; GAS CHROMATOGRAPHY;

AUTOMATED METHODS; DATA SET; DETECTION METHODS; GASCHROMATOGRAPHY-MASS SPECTROMETRY; MASS SPECTROMETRY DATA; MATCHING METHODS; METABOLOMICS; NEW APPROACHES; PEAK DETECTION; PEAK MATCHING;

MASS SPECTROMETRY;

EID: 34249299023     PISSN: 08869383     EISSN: 1099128X     Source Type: Journal    
DOI: 10.1002/cem.1005     Document Type: Article

References (40)

1. Kuhara T. Gas chromatographic-mass spectrometric urinary metabolome analysis to study mutations of inborn errors of metabolism. Mass. Spec. Rev. 2005; 24: 814-827.
2. Carrillo JD, López AG, Tena MT. Determination of volatile oak compounds in wine by headspace solid-phase microextraction and gas chromatography-mass spectrometry. J. Chromatogr. A 2006; 1102: 25-36.
3. Shen H, Carter JF, Brereton RG, Eckers C. Discrimination between tablet production methods using pyrolysis-gas chromatography-mass spectrometry and pattern recognition. Analyst 2003; 128: 287-292.
4. Service K, Brereton RG, Harris S. Analysis of badger urine volatiles using gas chromatography-mass spectrometry and pattern recognition techniques. Analyst 2001; 126: 615-623.
5. Mishra S, Tripathi RM, Bhalke S, Shukla VK, Puranik VD. Determination of methylmercury and mercury (II) in a marine ecosystem using solid-phase microextraction gas chromatography-mass spectrometry. Anal. Chim. Acta 2005; 551: 192-198.
6. Soini HA, Bruce KE, Klouckova I, Brereton RG, Penn DJ, Novotny MV. In-situ surface sampling of biological objects and preconcentration of their volatiles for chromatographic analysis. Anal. Chem. 2006; 78: 7161-7168.
7. Baltussen E, Cramers CA, Sandra PJ. Sorptive sample preparation - a review. Anal. Bioanal. Chem. 2002; 373: 3-22.
8. Gong F, Wang BT, Chau FT, Liang YZ. Data preprocessing for chromatographic fingerprint of herbal medicine with chemometric approaches. Anal. Letts. 2005; 38: 2475-2492.
9. Nielsen NPV, Carstensen JM, Smedsgaard J. Aligning of single and multiple wavelength chromatographic profiles for chemometric data analysis using correlation optimised warping. J. Chromatogr. A 1998; 805: 17-35.
10. Kassidas A, MacGregor JF, Taylor PA. Synchronization of batch trajectories using dynamic time warping. AIChE J. 1998; 44: 864-875.
11. Torgrip RJO, Åberg M, Karlberg B, Jacobsson SP. Peak alignment using reduced set mapping. J. Chemom. 2003; 17: 573-582.
12. Fraga CG, Prazen BJ, Synovec RE. Objective data alignment and chemometric analysis of comprehensive two-dimensional separations with run-to-run peak shifting on both dimensions. Anal. Chem. 2001; 73: 5833-5840.
13. Andersson R, Hämäläinen MD. Simplex focusing of retention times and latent variable projections of chromatographic profiles. Chemom. Intell. Lab. Syst. 1994; 22: 49-61.
14. Jonsson P, Bruce SJ, Moritz T, Trygg J, Sjöström M, Plumb R, Granger J, Maibaum E, Nicholson JK, Holmes E, Antti H. Extraction, interpretation and validation of information for comparing samples in metabolic LC/MS data sets. Analyst 2005; 130: 701-707.
15. Windig W, Phalp JM, Payne AW. A noise and background reduction method for component detection in liquid chromatography/mass spectrometry. Anal. Chem. 1996; 68: 3602-3606.
16. Hastings CA, Norton AM, Roy S. New algorithms for processing and peak detection in liquid chromatography/mass spectrometry data. Rapid Commun. Mass Spectrom. 2002; 16: 462-467.
17. Vivó-Truyols G, Torres-Lapasió JR, van Nederkassel AM, van der Heyden Y, Massart DL. Automatic program for peak detection and deconvolution of multioverlapped chromatographic signals, Part I, Peak detection. J. Chromatogr. A 2005; 1096: 133-145.
18. Jarman KH, Daly DS, Anderson KK, Wahl KL. A new approach to automated peak detection. Chemom. Intell. Lab. Sys. 2003; 69: 61-76.
19. Stein SE. An integrated method for spectrum extraction and compound identification from gas chromatography/mass spectrometry data. J. Am. Soc. Mass Spectrom. 1999; 10: 770-781.
20. Silva-Wilkinson RA, Burkhard LP, Sheedy BR, DeGraeve GM, Lordo RA. A simple comparison of mass spectral search results and implications for environmental screening analyses. Arch. Environ. Cont. Toxicol. 1999; 36: 109-114.
21. Pesyna GM, Venkataraghavan R, Dayringer HE, McLafferty FW. Probability based matching system using a large collection of reference mass spectra. Anal. Chem. 1976; 48: 1362-1368.
22. Stein SE, Scott DR. Optimization and testing of mass spectral library search algorithms for compound identification. J. Am. Soc. Mass. Spectrom. 1994; 5: 859-866.
23. Shen H, Grung B, Kvalheim OM, Eide I. Automated curve resolution applied to data from multi-detection instruments. Anal. Chim. Acta 2001; 446: 313-328.
24. Eide I, Neverdal G, Thorvaldsen B, Arneberg R, Grung B, Kvalheim OM. Toxicological evaluation of complex mixtures: fingerprinting and multivariate analysis. Environ. Toxicol. Pharmacol. 2004; 18: 127-133.
25. Jiang JH, Ozaki Y. Self-modeling curve resolution (SMCR), Principles, techniques, and applications. Appl. Spectrosc. Rev. 2002; 37: 321-345.
26. Idborg H, Edlund PO, Jacobsson SP. Multivariate approaches for efficient detection of potential metabolites from liquid chromatography/mass spectrometry data. Rapid Commun. Mass Spectrom. 2004; 18: 944-954.
27. Steffen B, Müller KP, Komenda M, Koppmann R, Schaub A. A new mathematical procedure to evaluate peaks in complex chromatograms. J. Chromatogr. A 2005; 1071: 239-246.
28. Jonsson P, Johansson AI, Gullberg J, Trygg JAJ, Grung B, Marklund S, Sjöström M, Antti H, Moritz T. High-throughput data analysis for detecting and identifying differences between samples in GC/MS-based metabolomic analyses. Anal. Chem. 2005; 77: 5635-5642.
29. Dixon SJ, Brereton RG, Carter JF, Sleeman R. Determination of cocaine contamination on banknotes using tandem mass spectrometry and pattern recognition. Anal. Chim. Acta 2006; 559: 54-63.
30. Jonsson P, Gulberg J, Nordström A, Kusano M, Kowalczyk M, Sjöström M, Moritz T. A strategy for identifying differences in large series of metabolomic samples analyzed by GC/MS. Anal. Chem. 2004; 76: 1738-1745.
31. Christensen JH, Mortensen J, Hansen AB, Andersen O. Chromatographic preprocessing of GC-MS data for analysis of complex chemical mixtures. J. Chromatogr. A 2005; 1062: 113-123.
32. Duran AL, Yang J, Wang LJ, Sumner LW. Metabolomics spectral formatting, alignment and conversion tools (MSFACTs). Bioinformatics 2003; 19: 2283-2293.
33. Dixon SJ, Xu Y, Brereton RG, Soini HA, Novotny MV, Oberzaucher E, Grammer K, Penn DJ. Chemom. Intell. lab. Sys. In press.
34. http://mexcdf.sourceforge.net/.
35. Windig W, Phalp JM, Payne AW. A noise and background reduction method for component detection in liquid chromatography/mass spectrometry. Anal. Chem. 1996; 68: 3602-3606.
36. Zomer S, Brereton RG, Wolff JC, Airiau CY, Smallwood C. Component detection weighted index of analogy: similarity recognition on liquid chromatographic mass spectral data for the characterization of route/process specific impurities in pharmaceutical tables. Anal. Chem. 2005; 77: 1607-1621.
37. Donoho DL. De-noising by soft thresholding. IEEE Trans. Inf. Theory 1995; 41: 613-627.
38. Special issue on wavelets. Proc. IEEE. 1996; 84: 507-685.
39. Savitzky A, Golay MJE. Smoothing and differentiation of data by simplified least squares procedures. Anal. Chem. 1964; 36: 1627-1639.
40. Brereton RG. Chemometrics: Data Analysis for the Laboratory and Chemical Plant. Wiley: Chichester, UK, 2003; p 132.