DA_2DCHROM - a data alignment tool for applications on real GC × GC-TOF samples
Status PubMed-not-MEDLINE Jazyk angličtina Země Německo Médium print-electronic
Typ dokumentu časopisecké články
Grantová podpora
VJ01010123
Ministerstvo Vnitra České Republiky
PubMed
37036485
PubMed Central
PMC10149467
DOI
10.1007/s00216-023-04679-7
PII: 10.1007/s00216-023-04679-7
Knihovny.cz E-zdroje
- Klíčová slova
- Data alignment algorithm, Data alignment automation, GC × GC–TOF real samples, Human scent,
- Publikační typ
- časopisecké články MeSH
Comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC × GC-MS) has great potential for analyses of complicated mixtures and sample matrices, due to its separation power and possible high resolution. The second component of the measurement results, the mass spectra, is reproducible. However, the reproducibility of two-dimensional chromatography is affected by many factors and makes the evaluation of long-term experiments or cross-laboratory collaborations complicated. This paper presents a new open-source data alignment tool to tackle the problem of retention time shifts - with 5 different algorithms implemented: BiPACE 2D, DISCO, MSort, PAM, and TNT-DA, along with Pearson's correlation and dot product as optional methods for mass spectra comparison. The implemented data alignment algorithms and their variations were tested on real samples to demonstrate the functionality of the presented tool. The suitability of each implemented algorithm for significantly/non-significantly shifted data was discussed on the basis of the results obtained. For the evaluation of the "goodness" of the alignment, Kolmogorov-Smirnov test values were calculated, and comparison graphs were generated. The DA_2DChrom is available online with its documentation, fully open-sourced, and the user can use the tool without the need of uploading their data to external third-party servers.
Zobrazit více v PubMed
Liu Z, Phillips JB. Comprehensive two-dimensional gas chromatography using an on-column thermal modulator interface. J Chromatogr Sci. 1991;29(6):227–231. doi: 10.1093/chromsci/29.6.227. DOI
Myronenko A, Song X. Point set registration: coherent point drift. IEEE T Pattern Anal. 2010;32(12):2262–2275. doi: 10.1109/TPAMI.2010.46. PubMed DOI
Deng B, Kim S, Li H, Heath E, Zhang X. Global peak alignment for comprehensive two-dimensional gas chromatography mass spectrometry using point matching algorithms. J Bioinf Comput Biol. 2016;14(6):1650032. doi: 10.1142/S0219720016500323. PubMed DOI PMC
Li Z, Kim S, Zhong S, Zhong Z, Kato I, Zhang X. Coherent point drift peak alignment algorithms using distance and similarity measures for two-dimensional gas chromatography mass spectrometry data. J Chemometr. 2020;34(8):e3236. doi: 10.1002/cem.3236. PubMed DOI PMC
Zhang D, Huang X, Regnier FE, Zhang M. Two-dimensional correlation optimized warping algorithm for aligning GC×GC−MS data. Anal Chem. 2008;80(8):2664–2671. doi: 10.1021/ac7024317. PubMed DOI
Tomasi G, van den Berg F, Andersson C. Correlation optimized warping and dynamic time warping as preprocessing methods for chromatographic data. J Chemometr. 2004;18(5):231–241. doi: 10.1002/cem.859. DOI
Gros J, Nabi D, Dimitriou-Christidis P, Rutler R, Arey JS. Robust algorithm for aligning two-dimensional chromatograms. Anal Chem. 2012;84(21):9033–9040. doi: 10.1021/ac301367s. PubMed DOI
Reichenbach SE, Rempe DW, Tao Q, Bressanello D, Liberto E, Bicchi C, et al. Alignment for comprehensive two-dimensional gas chromatography with dual secondary columns and detectors. Anal Chem. 2015;87(19):10056–10063. doi: 10.1021/acs.analchem.5b02718. PubMed DOI
Kim S, Koo I, Fang A, Zhang X. Smith-Waterman peak alignment for comprehensive two-dimensional gas chromatography-mass spectrometry. BMC Bioinf. 2011;12(1):235. doi: 10.1186/1471-2105-12-235. PubMed DOI PMC
Smith TF, Waterman MS. Identification of common molecular subsequences. J Mol Biol. 1981;147(1):195–197. doi: 10.1016/0022-2836(81)90087-5. PubMed DOI
Robinson MD, De Souza DP, Keen WW, Saunders EC, McConville MJ, Speed TP, et al. A dynamic programming approach for the alignment of signal peaks in multiple gas chromatography-mass spectrometry experiments. BMC Bioinf. 2007;8(1):419. doi: 10.1186/1471-2105-8-419. PubMed DOI PMC
Hoffmann N, Wilhelm M, Doebbe A, Niehaus K, Stoye J. BiPACE 2D—graph-based multiple alignment for comprehensive 2D gas chromatography-mass spectrometry. Bioinf. 2013;30(7):988–995. doi: 10.1093/bioinformatics/btt738. PubMed DOI
Wang B, Fang A, Heim J, Bogdanov B, Pugh S, Libardoni M, et al. DISCO: distance and spectrum correlation optimization alignment for two-dimensional gas chromatography time-of-flight mass spectrometry-based metabolomics. Anal Chem. 2010;82(12):5069–5081. doi: 10.1021/ac100064b. PubMed DOI PMC
Oh C, Huang X, Regnier FE, Buck C, Zhang X. Comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry peak sorting algorithm. J Chromatogr A. 2008;1179(2):205–215. doi: 10.1016/j.chroma.2007.11.101. PubMed DOI PMC
Kim S, Fang A, Wang B, Jeong J, Zhang X. An optimal peak alignment for comprehensive two-dimensional gas chromatography mass spectrometry using mixture similarity measure. Bioinf. (Oxford, England) 2011;27(12):1660–1666. doi: 10.1093/bioinformatics/btr188. PubMed DOI PMC
Ladislavová; N. DA_2DCHROM - data alignment. 1.0 ed: Zenodo; 2022. 10.5281/zenodo.7040975
Kim S, Koo I, Jeong J, Wu S, Shi X, Zhang X. Compound identification using partial and semipartial correlations for gas chromatography–mass spectrometry data. Anal Chem. 2012;84(15):6477–6487. doi: 10.1021/ac301350n. PubMed DOI PMC
Ladislavová N, Pojmanová P. DA_2DCHROM - sample dataset. In: Zenodo, editor. 2022. 10.5281/zenodo.7068336
Pojmanová P, Ladislavová N. 2DGCTOF Human Skin scent samples dataset. In: Zenodo, editor. 1.0 ed2022. 10.5281/zenodo.7307846
Pojmanová P, Ladislavová N, Urban Š. Development of a method for the measurement of human scent samples using comprehensive two-dimensional gas chromatography with mass detection. Separations. 2021;8(12):232. doi: 10.3390/separations8120232. DOI
Justel A, Peña D, Zamar R. A multivariate Kolmogorov-Smirnov test of goodness of fit. Stat Probabil Lett. 1997;35(3):251–259. doi: 10.1016/S0167-7152(97)00020-5. DOI
Powers DM. Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation. arXiv preprint arXiv:201016061. 2020. 10.48550/arXiv.2010.16061
Stein SE, Scott DR. Optimization and testing of mass spectral library search algorithms for compound identification. J Am Soc Mass Spectr. 1994;5(9):859–866. doi: 10.1016/1044-0305(94)87009-8. PubMed DOI