Lingli Deng1, 2, Jiyang Dong1, Zhong Chen1, 2
1Department of Electronic Science, Xiamen University, Xiamen, Fujian, China; 2Department of Communication Engineering, Xiamen University, Xiamen, Fujian, China
Scaling is an important data preprocessing procedure prior to multivariate statistical analysis for NMR spectroscopic metabolomics. The commonly used methods scale each variable of the data independently, which ignores the chemical meaning of the spectra and may make the subsequent analysis be hard to interpret. A new scaling method based on non-negative principal component analysis (NPCA) is proposed in this paper. It aims to perform scaling on the concentration of the metabolites rather than on the variables. Analysis results of simulated and real 1H NMR spectra presents itself as an interpretable pretreatment method for multivariable data analysis.