分析谱图和色谱数据的新方法
会议Poster
A Novel Method of Analyzing Spectral and Chromatographic Data
Abstract
Traditionally, the visualization of multiple spectra or chromatograms takes place in an overlay, offset, or stacked plotting form. A new technology known as Overlap Density (OD) Heatmaps reverses this situation by allowing comparative visualization of the overlap of large numbers of spectra or chromatograms so that trends and other useful information can be discerned. OD Heatmaps allows the user to explore data similarities and dissimilarities in large databases by providing information about the most and/or least commonly occurring spectral or chromatographic features in a data set(s). In this study, a new approach for spectral and
chromatographic analysis that combines this new technology with chemometrics tools for multivariate analyses will be examined incorporating multiple analytical techniques in various application areas. The use of methods such as Principal Component Analysis (PCA) to perform multivariate analyses on spectral and chromatographic data has used for years in the field of analytical chemistry. This new approach for spectroscopic analysis will be examined in specific case studies. We will demonstrate the successful use of PCA and Overlap Density Heatmaps to analyze a query and the hit list from a spectral search and perform an overall analysis of a database.
Conclusions
Principal Component Analysis is a valuable tool to analyze the results of standard spectral searches (i.e. a spectral query and hit list) and provides useful insights into the nature of the compounds in the hit list relative to the query. Overlap Density (OD) Heatmaps not only confirm the value of the technique, but are also a useful complement to the multivariate processing capabilities afforded by PCA.