Carotta: Revealing hidden confounder markers in metabolic breath profiles

Metabolites

Volumn 5, Issue 2, 2015, Pages 344-363

  Hauschild, Anne Christin ^a,b   Frisch, Tobias ^a,c   Baumbach, Jörg Ingo ^d   Baumbach, Jan ^b  

^a MAX PLANCK INSTITUTE FOR INFORMATICS   (Germany)

^b UNIVERSITY OF SOUTHERN DENMARK   (Denmark)

^c FREIE UNIVERSITÄT BERLIN   (Germany)

^d REUTLINGEN UNIVERSITY   (Germany)

Author keywords

Breath analysis; Breathomics; Clustering; Multicapillary column ion mobility spectrometry

Indexed keywords

MENTHOL; VOLATILE ORGANIC COMPOUND;

ARTICLE; BREATH ANALYSIS; BREATHING; CAROTTA; CHRONIC OBSTRUCTIVE LUNG DISEASE; CLUSTER ANALYSIS; DATA ANALYSIS SOFTWARE; EXPIRED AIR; HUMAN; ION MOBILITY SPECTROMETRY; LUNG CARCINOMA; MASS FRAGMENTOGRAPHY; MASS SPECTROMETRY; METABOLITE; MULTIDIMENSIONAL SCALING; NUTRITION; PROTON TRANSFER REACTION MASS SPECTROMETRY; SMOKING;

EID: 85016913180     PISSN: None     EISSN: 22181989     Source Type: Journal    
DOI: 10.3390/metabo5020344     Document Type: Article

References (61)

1. Hauschild, A.C.; Frisch, T.; Baumbach, J.I.; Baumbach, J. University of Southn Denmark. Carotta-Revealing Hidden Confounder Markers in Metabolic Breath Profiles. 2015. Available online: http://carotta.compbio.sdu.dk (accessed on 31 May 2015).
2. Pereira, J.; Porto-Figueira, P.; Cavaco, C.; Taunk, K.; Rapole, S.; Dhakne, R.; Nagarajaram, H.; Camara, J.S. Breath analysis as a potential and non-invasive frontier in disease diagnosis: An overview. Metabolites 2015, 5, 3-55.
3. Ligor, T.; Ligor, M.; Amann, A.; Ager, C.; Bachler, M.; Dzien, A.; Buszewski, B. The analysis of healthy volunteers' exhaled breath by the use of solid-phase microextraction and GC-MS. J. Breath Res. 2008, 2, 046006:1-046006:8.
4. Juenger, M.; Boedeker, B.; Baumbach, J. Peak assignment in multi-capillary column-ion mobility spectrometry using comparative studies with gas chromatography-mass spectrometry for exhalred breath analysis. Anal. Bioanal. Chem. 2010, 396, 471-482.
5. Mieth, M.; Schubert, J.K.; Groger, T.; Sabel, B.; Kischkel, S.; Fuchs, P.; Hein, D.; Zimmermann, R.; Miekisch, W. Automated Needle Trap Heart-Cut GC/MS and Needle Trap Comprehensive Two-Dimensional GC/TOF-MS for Breath Gas Analysis in the Clinical Environment. Anal. Chem. 2010, 82, 2541-2551.
6. Cheng, Z.J.; Warwick, G.; Yates, D.H.; Thomas, P.S. An electronic nose in the discrimination of breath from smokers and non-smokers: A model for toxin exposure. J. Breath Res. 2009, 3, 036003:1-036003:5.
7. Dragonieri, S.; Annema, J.T.; Schot, R.; van der Schee, M.P.C.; Spanevello, A.; Carratu, P.; Resta, O.; Rabe, K.F.; Sterk, P.J. An electronic nose in the discrimination of patients with non-small cell lung cancer and COPD. Lung Cancer 2009, 64, 166-170.
8. Beauchamp, J.; Kirsch, F.; Buettner, A. Real-time breath gas analysis for pharmacokinetics: Monitoring exhaled breath by on-line proton-transfer-reaction mass spectrometry after ingestion of eucalyptol-containing capsules. J. Breath Res. 2010, 4. CAPLUS AN 2010:699470(Journal; Online Computer File).
9. Herbig, J.; Mueller, M.; Schallhart, S.; Titzmann, T.; Graus, M.; Hansel, A. On-line breath analysis with PTR-TOF. J. Breath Res. 2009, 3, 027004:1-027004:10.
10. Westhoff, M.; Litterst, P.; Maddula, S.; Bödeker, B.; Baumbach, J.I. Statistical and bioinformatical methods to differentiate chronic obstructive pulmonary disease (COPD) including lung cancer from healthy control by breath analysis using ion mobility spectrometry. Int. J. Ion Mobil. Spectrom. 2011, 14, 139-149.
11. Hauschild, A.; Baumbach, J.I. Integrated statistical learning of metabolic ion mobility spectrometry profiles for pulmonary disease identification. Genet. Mol. Res. 2012, 11, 2733-2744.
12. Baumbach, J.I.; Westhoff, M. Ion mobility spectrometry to detect lung cancer and airway infections. Spectrosc. Eur. 2006, 18, 22-27.
13. Westhoff, M.; Litterst, P.; Freitag, L.; Baumbach, J. Ion mobility spectrometry in the diagnosis of Sarcoidosis: Results of a feasibility study. J. Physiol. Pharmacol. 2007, 58, 739-751.
14. Vautz, W.; Nolte, J.; Fobbe, R.; Baumbach, J. Breath analysis-performance and potential of ion mobility spectrometry. J. Breath Res. 2009, 3, doi:10.1088/1752-7155/3/3/036004.
15. Steeghs, M.M.L.; Cristescu, S.M.; Harren, F.J.M. The suitability of Tedlar bags for breath sampling in medical diagnostic research. Physiol. Meas. 2007, 28, 73-84.
16. Baumbach, J.; Eiceman, G. Ion Mobility Spectrometry: Arriving On Site and Moving Beyond a Low Profile. Appl. Spectrosc. 1999, 53, 338A-355A.
17. Hill, H.H.; Siems, W.F.; Stlouis, R.H.; McMinn, D.G. Ion Mobility Spectrometry. Anal. Chem. 1990, 62, A1201-A1209.
18. Ruzsanyi, V.; Baumbach, J.I.; Sielemann, S.; Litterst, P.; Westhoff, M.; Freitag, L. Detection of human metabolites using multi-capillary columns coupled to ion mobility spectrometers. J. Chromatogr. A 2005, 1084, 145-151.
19. Baumbach, J.I. Ion mobility spectrometry coupled with multi-capillary columns for metabolic profiling of human breath. J. Breath Res. 2009, 3, 1-16.
20. Fink, T.; Baumbach, J.I.; Kreuer, S. Ion mobility spectrometry in breath research. J. Breath Res. 2014, 8, 027104.
21. Maddula, S.; Blank, L.; Schmid, A.; Baumbach, J. Detection of volatile metabolites of Escherichia coli by multi capillary column coupled ion mobility spectrometry. Anal. Bioanal. Chem. 2009, 394, 791-800.
22. Bödeker, B.; Vautz, W.; Baumbach, J.I. Peak finding and referencing in MCC/IMS-data. Int. J. Ion Mobil. Spectrom. 2008, 11, 83-87.
23. Bader, S. Identification and Quantification of Peaks in Spectrometric Data. Ph.D. Thesis, TU Dortmund, Dortmund, Germany, 2008.
24. Hauschild, A.; Schneider, T.; Pauling, J.; Rupp, K.; Jang, M.; Baumbach, J.I.; Baumbach, J. Computational Methods for Metabolomic Data Analysis of Ion Mobility Spectrometry Data-Reviewing the State of the Art. Metabolites 2012, 2, 733-755.
25. Smolinska, A.; Hauschild, A.; Fijten, R.; Dallinga, J.; Baumbach, J.; van Schooten, F. Current breathomics ? A review on data pre-processing techniques and machine learning in metabolomics breath analysis. J. Breath Res. 2014, 8, 027105.
26. Eckel, S.P.; Baumbach, J.; Hauschild, A.C. On the importance of statistics in breath analysis - hope or curse? J. Breath Res. 2014, 8, 012001.
27. Meyer, N.; Dallinga, J.W.; Nuss, S.; Moonen, E.; van Berkel, J.; Akdis, C.; van Schooten, F.; Menz, G. Defining adult asthma endotypes by clinical features and patterns of volatile organic compounds in exhaled air. Respir. Res. 2014, 15, 136.
28. Broza, Y.Y.; Zuri, L.; Haick, H. Combined volatolomics for monitoring of human body chemistry. Sci. Rep. 2014, 4, 4611.
29. Fens, N.; van Rossum, A.G.; Zanen, P.; van Ginneken, B.; van Klaveren, R.J.; Zwinderman, A.H.; Sterk, P.J. Subphenotypes of mild-to-moderate COPD by factor and cluster analysis of pulmonary function, CT imaging and breathomics in a population-based survey. COPD 2013, 10, 277-285.
30. Hall, M.; Frank, E.; Holmes, G.; Pfahringer, B.; Reutemann, P.; Witten, I.H. The WEKA data mining software: An update. ACM SIGKDD Explor. Newsl. 2009, 11, 10-18.
31. Mierswa, I.; Wurst, M.; Klinkenberg, R.; Scholz, M.; Euler, T. Yale: Rapid prototyping for complex data mining tasks. In Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Philadelphia, PA, USA, 20-23 August, 2006; ACM: New York, NY, USA, 2006, pp. 935-940.
32. Ihaka, R.; Gentleman, R. R: A language for data analysis and graphics. J. Comput. Gr. Stat. 1996, 5, 299-314.
33. Bro, R.; Papalexakis, E.E.; Acar, E.; Sidiropoulos, N.D. Coclustering-a useful tool for chemometrics. J. Chemom. 2012, 26, 256-263.
34. Sun, P.; Speicher, N.K.; Rottger, R.; Guo, J.; Baumbach, J. Bi-Force: Large-scale bicluster editing and its application to gene expression data biclustering. Nucl. Acids Res. 2014, 42, e78.
35. Merkl, R.; Waack, S. Bioinformatik Interaktiv; Wiley-VCH Verlag GmbH & Co. KGaA: Weinheim, Germany, 2009.
36. Zerzucha, P.; Walczak, B. Concept of (dis)similarity in data analysis. TrAC Trends Anal. Chem. 2012, 38, 116-128.
37. Hastie, T.; Tibshirani, R.; Friedman, J.J.H. The Elements of Statistical Learning; Springer: New York, NY, USA, 2001; Volume 1.
38. Wittkop, T. Clustering Biological Data by Unraveling Hidden Transitive Substructures; Bielefeld University: Bielefeld, Germany, 2010.
39. Wittkop, T.; Emig, D.; Lange, S.; Rahmann, S.; Albrecht, M.; Morris, J.H.; Böcker, S.; Stoye, J.; Baumbach, J. Partitioning biological data with transitivity clustering. Nat. Methods 2010, 7, 419-420.
40. Sape-Research-Group. Hac - A Java class library for hierarchical agglomerative clustering. 2014. Available online: http://sape.inf.usi.ch/hac/ (accessed on 26 February 2015).
41. Java Excel API - A Java API to read, write, and modify Excel spreadsheets, Available online: http://jexcelapi.sourceforge.net/ (accessed on 20 September 2013).
42. Gilbert, D.; Morgner, T. JFreeChart. 2005. Available online: http://www.jfree.org/jfreechart/ index.html (accessed on 20 September 2013).
43. JHeatChart-Java library for generating heat map charts, Available online: http://www.javaheatmap.com/ (accessed on 20 September 2013).
44. Algorithmics-Group. MDSJ: Java Library for Multidimensional Scaling (Version 0.2), 2009. Available online: http://www.inf.uni-konstanz.de/algo/software/mdsj/ (accessed on 26 February 2015).
45. Google Core Libraries, Available online: https://code.google.com/p/guava-libraries/wiki/Release16 (accessed on 26 February 2015).
46. Chiba, S. Javassist (Java Programming Assistant), 2014. Available online: http://www.csg. ci.i.u-tokyo.ac.jp/chiba/javassist/ (accessed on 26 February 2015).
47. log4j 2.0, Apache Software Foundation, 2014. Available online: http://logging.apache.org/log4j/2.x/ (accessed on 26 February 2015).
48. Global Initiative for Chronic Obstructive Lung Disease. Global Strategy for Diagnosis, Management, and Prevention of COPD: update 2013. Available online: http://www.goldcopd.org/uploads/users/files/GOLD_Report_2013Feb13.pdf (accessed on 26 September 2013).
49. World Health Organization. Available online: http://www.who.int/en/ (accessed on 26 September 2013).
50. Young, R.P.; Hopkins, R.J.; Christmas, T.; Black, P.N.; Metcalf, P.; Gamble, G. COPD prevalence is increased in lung cancer, independent of age, sex and smoking history. Eur. Respir. J. 2009, 34, 380-386.
51. National Cancer Institute, Available online: www.cancer.gov (accessed on 26 September 2013).
52. Westhoff, M.; Litterst, P.; Maddula, S.; Bödeker, B.; Baumbach, J. Statistical and bioinformatical methods to differentiate chronic obstructive pulmonary disease (COPD) including lung cancer from healthy control by breath analysis using ion mobility spectrometry. Int. J. Ion Mobil. Spectrom. 2011, 14, 139-149.
53. Spearman, C. The Proof and Measurement of Association between Two Things. Am. J. Psychol. 1904, 15, 72-101.
54. Rousseeuw, P.J. Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math. 1987, 20, 53-65.
55. Paccanaro, A.; Casbon, J.A.; Saqi, M.A. Spectral clustering of protein sequences. Nucl. Acids Res. 2006, 34, 1571-1580.
56. Kruskal, J.B. Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika 1964, 29, 1-27.
57. Pluskal, T.; Castillo, S.; Villar-Briones, A.; Oresic, M. MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data. BMC Bioinform. 2010, doi:10.1186/1471-2105-11-395.
58. Kessler, N.; Neuweger, H.; Bonte, A.; Langenkamper, G.; Niehaus, K.; Nattkemper, T.W.; Goesmann, A. MeltDB 2.0-advances of the metabolomics software system. Bioinformatics 2013, 29, 2452-2459.
59. Gowda, H.; Ivanisevic, J.; Johnson, C.H.; Kurczy, M.E.; Benton, H.P.; Rinehart, D.; Nguyen, T.; Ray, J.; Kuehl, J.; Arevalo, B.; et al. Interactive XCMS Online: Simplifying advanced metabolomic data processing and subsequent statistical analyses. Anal. Chem. 2014, 86, 6931-6939.
60. Xia, J.; Mandal, R.; Sinelnikov, I.V.; Broadhurst, D.; Wishart, D.S. MetaboAnalyst 2.0-a comprehensive server for metabolomic data analysis. Nucl. Acids Res. 2012, 40, W127-W133.
61. D'Addario, M.; Kopczynski, D.; Baumbach, J.I.; Rahmann, S. A modular computational framework for automated peak extraction from ion mobility spectra. BMC Bioinform. 2014, doi:10.1186/1471-2105-15-25.