Yao Weifeng, Yin Xiaoying, Hu Yuzhu
Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, Nanjing 210009, China.
J Chromatogr A. 2007 Aug 10;1160(1-2):254-62. doi: 10.1016/j.chroma.2007.05.061. Epub 2007 May 25.
The alignment of chromatographic signals is an important preprocessing step before further multivariate analysis. This paper presents a method, automated peak alignment by beam search (Auto-PABS), to solve the problem of peak shift in chemical chromatographic fingerprints by piecewise shifting and linearly interpolating. It is characterized by searching an adaptive range for the values of shifting and linearly interpolating of each segment. This search range is estimated by the calculation of fast Fourier transform cross correlation between the sample segment and its corresponding reference segment. Thus, arbitrary peak alignment is avoided when the real peak shifts are unknown in a large data set. Since the maximum of search range is close to the real shift, more accurate beam search is adopted to accomplish the optimization process. Simulated data and herbal medicine fingerprints of HPLC and GC are selected for evaluation. The output matrix of aligned chromatographic profiles is used directly for principal components analysis, yielding satisfactory results on real samples.
色谱信号对齐是进一步进行多变量分析之前的一个重要预处理步骤。本文提出了一种通过束搜索进行自动峰对齐（Auto-PABS）的方法，以解决化学色谱指纹图谱中的峰漂移问题，该方法通过分段移位和线性插值来实现。其特点是为每个段的移位和线性插值值搜索一个自适应范围。这个搜索范围是通过计算样本段与其相应参考段之间的快速傅里叶变换互相关来估计的。因此，当在大数据集中真实峰漂移未知时，可以避免任意峰对齐。由于搜索范围的最大值接近真实移位，因此采用更精确的束搜索来完成优化过程。选择了模拟数据以及HPLC和GC的草药指纹图谱进行评估。对齐后的色谱图输出矩阵直接用于主成分分析，在实际样品上取得了令人满意的结果。
