Application of principal component analysis to detect outliers and spectral deviations in near-field surface-enhanced Raman spectra
Application of principal component analysis to detect outliers and spectral deviations in near-field surface-enhanced Raman spectra
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DOI：
10.1016/s0003-2670(01)01267-3
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发表时间：
2001-11-19
影响因子：
6.2
通讯作者：
Zenobi, R
中科院分区：
文献类型：
--
作者：
de Groot, PJ;Postma, GJ;Zenobi, R
最近开发的技术措施近场表面增强拉曼光谱与100纳米的分辨率，使样品表面上的快速调查。这种技术有两个瓶颈：一个是一个普遍的问题：信号变化归因于样品成分或衬底形态。因此，为了区分这两种效应，必须检测甚至很小的信号变化。其次，庞大的数据量使得频谱解释繁琐。如何找到有趣和重要的信息？为了研究这些问题，测量含有滴涂到银岛基底上的染料标记的DNA片段的样品。增强的拉曼光谱产生关于DNA片段的间接信息。本研究的目的是提供一种工具，允许快速和可靠的光谱分析。是否有可能区分样品成分的局部差异，并将其与样品形态相关联？一个一般的探索性数据分析工具，主成分分析（PCA），用于第一次调查。PCA有一个有用的副作用：尖峰，众所周知的文物，也被检测到。在去除这些伪影后，PCA促进了三个相邻光谱的检测，明显偏离其他光谱。很可能，DNA双链展开并产生直接的拉曼信号。自动PCA程序给出了相同的结果。它的结论是，一个通用的探索工具可以解决两个主要的困难。专用化学计量学工具的应用可以改善结果。将化学计量学与这一新技术相结合，是一种很有前途的方法。(C)2001 Elsevier Science B.V.保留所有权利。
A recently developed technique measures near-field surface-enhanced Raman spectra with 100-nm resolution, enabling a fast survey on the sample surface. This technique has two bottlenecks One is a general problem: signal changes are attributed to either the sample composition or the substrate morphology. Therefore, it is mandatory to detect even small signal changes in order to distinguish between these two effects. Secondly, huge data amounts make the spectrum interpretation tedious. How to find the interesting and important information? To investigate these problems, a sample, containing dye-labeled DNA-fragments that are drop-coated onto a silver island substrate, is measured. The enhanced Raman spectra yield indirect information on the DNA-fragments. The goal of this investigation is to provide a tool that allows a fast and reliable spectral analysis. Is it possible to distinguish local differences in the sample composition and to correlate them with the sample morphology?A general explorative data analyses tool, principal component analysis (PCA), is used for a first investigation. PCA has a useful side-effect: spikes, well-known artifacts, are also detected. After removing these artifacts, PCA facilitated the detection of three neighboring spectra, clearly deviating from the others. Probably, the DNA double-strand unfolded and generated a direct Raman-signal. The automated PCA-procedure gives identical results. It is concluded that a general explorative tool can solve two major difficulties. Application of dedicated chemometrical tools could improve the results. The combination of chemometrics and this new technique is powerful and promising. (C) 2001 Elsevier Science B.V. All rights reserved.