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      Application of fast Fourier transform cross-correlation for the alignment of large chromatographic and spectral datasets.

      Analytical Chemistry
      Algorithms, Chromatography, Gas, Databases as Topic, Fourier Analysis, Mass Spectrometry, Time Factors

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          Abstract

          Preprocessing of chromatographic and spectral data is an important aspect of analytical sciences. In particular, recent advances in proteomics have resulted in the generation of large data sets that require analysis. To assist accurate comparison of chemical signals, we propose two methods for the alignment of multiple spectral data sets. Based on methods previously described, each chromatograph or spectrum to be aligned is divided and aligned as individual segments to a reference. However, our methods make use of fast Fourier transform for the rapid computation of a cross-correlation function that enables alignments between samples to be optimized. The proposed methods are demonstrated in comparison with an existing method on a chromatographic and a mass spectral data set. It is shown that our methods provide an advantage of speed and a reduction of the number of input parameters required. The software implementations for the proposed alignment methods are available under the downloads section at http://ptcl.chem.ox.ac.uk/~jwong/specalign.

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          Author and article information

          Journal
          16131078
          10.1021/ac050619p

          Chemistry
          Algorithms,Chromatography, Gas,Databases as Topic,Fourier Analysis,Mass Spectrometry,Time Factors

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