NMR spectral quantitation by principal component analysis

被引:74
作者
Stoyanova, R [1 ]
Brown, TR [1 ]
机构
[1] Fox Chase Canc Ctr, Philadelphia, PA 19111 USA
关键词
peak parameters; spectral estimation; line shape correction;
D O I
10.1002/nbm.700
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
The use of principal component analysis (PCA) for simultaneous spectral quantitation of a single resonant peak across a series of spectra has gained popularity among the NMR community. The approach is fast, requires no assumptions regarding the peak lineshape and provides quantitation even for peaks with very low signal-to-noise ratio. PCA produces estimates of all peak parameters: area, frequency, phase and linewidth. If desired, these estimates can be used to correct the original data so that the peak in all spectra has the same lineshape. This ability makes PCA useful not only for direct peak quantitation, but also for processing spectral data prior to application of pattern recognition/classification techniques. This article briefly reviews the theoretical basis of PCA for spectral quantitation, addresses issues of data processing prior to PCA, describes suitable and unsuitable datasets for PCA applications and summarizes the developments and the limitations of the method. Copyright (C) 2001 John Wiley & Sons, Ltd.
引用
收藏
页码:271 / 277
页数:7
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