期刊
JOURNAL OF MAGNETIC RESONANCE
卷 202, 期 2, 页码 190-202出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jmr.2009.11.012
关键词
Preprocessing; NMR; Alignment; Metabonomics; Chemometrics; Algorithm
资金
- Danish Ministry of Food, Agriculture and Fisheries [3304-FVFP-060706-01]
- Villum Kann Rasmussen
- EU [MTKI-CT-2005-030056]
The increasing scientific and industrial interest towards metabonomics takes advantage from the high qualitative and quantitative information level of nuclear magnetic resonance (NMR) spectroscopy. However, several chemical and physical factors Can affect the absolute and the relative position of an NMR signal and it is not always possible OF desirable to eliminate these effects a priori. To remove misalignment of NMR signals a posteriori, several algorithms have been proposed in the literature. The icoshift program presented here is an open Source and highly efficient program designed for solving signal alignment problems in metabonomic NMR data analysis. The icoshift algorithm is based on correlation shifting of spectral intervals and employs an FFT engine that aligns all spectra simultaneously. The algorithm is demonstrated to be faster than similar methods found in the literature making full-resolution alignment of large datasets feasible and thus avoiding down-sampling steps such as binning. The algorithm uses missing values as a filling alternative in order to avoid spectral artifacts at the segment boundaries. The algorithm is made open source and the Matlab code including documentation can be downloaded from www.models.life.ku.dk. (C) 2009 Elsevier Inc. All rights reserved.
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