Quality & Technology, Department of Food Science, Faculty of Life Sciences, University of Copenhagen, Rolighedsvej 30, 1958 Frederiksberg C, Denmark.
J Magn Reson. 2010 Feb;202(2):190-202. doi: 10.1016/j.jmr.2009.11.012. Epub 2009 Nov 18.
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 or 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.
代谢组学日益引起科学界和工业界的兴趣，这得益于核磁共振（NMR）光谱具有的高质量和高通量信息水平。然而，一些化学和物理因素会影响 NMR 信号的绝对和相对位置，而且并不总是可以或期望预先消除这些影响。为了事后消除 NMR 信号的不对准，可以使用几种算法。本文提出的 icoshift 程序是一个开源的、高效的程序，旨在解决代谢组学 NMR 数据分析中的信号对准问题。icoshift 算法基于谱区间的相关移位，并采用 FFT 引擎来同时对齐所有谱。该算法比文献中发现的类似方法更快，从而使对大型数据集进行全分辨率对准成为可能，避免了下采样步骤，如分箱。该算法使用缺失值作为填充替代，以避免在分段边界处出现光谱伪影。该算法是开源的，包括文档的 Matlab 代码可以从 www.models.life.ku.dk 下载。
