Quantification of chromatographic data using a matched filter: robustness towards noise model errors

Bogaert, B. van den; Boelens, H.F.M.; Smit, H.C.

doi:10.1016/0003-2670(93)80608-n

Cited by 9 publications

(2 citation statements)

References 7 publications

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“…The application of a matched filtration approach to denoising in chromatography (with UV detection) was demonstrated over a decade ago, − where the Gaussian function was assumed to characterize the chromatographic peak shape. The cases of both white noise ( P N N = const) 13,14 and colored noise ( P NN proportional to 1/ f ) 15,16 were examined .…”

Section: Theorymentioning

confidence: 99%

“…The cases of both white noise ( P N N = const) 13,14 and colored noise ( P NN proportional to 1/ f ) 15,16 were examined . Cross-correlation with the Gaussian was shown to be robust to the errors in the presumed peak width 14 (e.g., a 2-fold error in peak width resulted in only a 10% decrease in S/N) and to errors in the noise model . The gain G in S/N due to the matched filtration of a Gaussian peak is equal to 8 where n is the number of data points per chromatographic peak.…”

Section: Theorymentioning

confidence: 99%

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A Universal Denoising and Peak Picking Algorithm for LC−MS Based on Matched Filtration in the Chromatographic Time Domain

et al. 2003

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A new denoising and peak picking algorithm (MEND, matched filtration with experimental noise determination) for analysis of LC-MS data is described. The algorithm minimizes both random and chemical noise in order to determine MS peaks corresponding to sample components. Noise characteristics in the data set are experimentally determined and used for efficient denoising. MEND is shown to enable low-intensity peaks to be detected, thus providing additional useful information for sample analysis. The process of denoising, performed in the chromatographic time domain, does not distort peak shapes in the m/z domain, allowing accurate determination of MS peak centroids, including low-intensity peaks. MEND has been applied to denoising of LC-MALDI-TOF-MS and LC-ESI-TOF-MS data for tryptic digests of protein mixtures. MEND is shown to suppress chemical and random noise and baseline fluctuations, as well as filter out false peaks originating from the matrix (MALDI) or mobile phase (ESI). In addition, MEND is shown to be effective for protein expression analysis by allowing selection of a large number of differentially expressed ICAT pairs, due to increased signal-to-noise ratio and mass accuracy.

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Section: Theorymentioning

confidence: 99%

Section: Theorymentioning

confidence: 99%

A Universal Denoising and Peak Picking Algorithm for LC−MS Based on Matched Filtration in the Chromatographic Time Domain

et al. 2003

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Quantification of overlapping chromatographic peaks using a matched filter

Bogaert

Boelens

Smit

1994

Chemometrics and Intelligent Laboratory Systems

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A novel approach to the quantification of overlapping chromatographic peaks is introduced. The sum of the models for the individual overlapping peaks is taken as the signal model in a matched filter. Thus, the signal intensities being the objective of the quantification procedure become parameters in an overall signal model. These and, if necessary, other parameters are adapted by a modified simplex algorithm optimizing the maximum in the output of the matched filter. A prediction of the results can be made on the basis of a noiseless response surface that can be calculated from the models. When shapes and positions of the peaks are known and only their intensities need to be estimated, a quantitative theoretical error estimation is possible. The results thus predicted are considered optimal and are used as a reference in the evaluation of the results of a range of experiments using simulated data containing two overlapping Gaussians and first-order band-limited noise. The proposed procedure works well, the quality of the results usually being on or just little below the theoretical optimum. Under conditions of high overlap or a low signal to noise ratio, the experimental results no longer follow a normal distribution and their quality is lower.

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Parametric studies of matched filters to enhance the signal-to-noise ratios of LC–MS–MS peaks

Wang

Chiang

Huang

2006

Analytica Chimica Acta

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Quantification of chromatographic data using a matched filter: robustness towards noise model errors

Cited by 9 publications

References 7 publications

A Universal Denoising and Peak Picking Algorithm for LC−MS Based on Matched Filtration in the Chromatographic Time Domain

A Universal Denoising and Peak Picking Algorithm for LC−MS Based on Matched Filtration in the Chromatographic Time Domain

Quantification of overlapping chromatographic peaks using a matched filter

Parametric studies of matched filters to enhance the signal-to-noise ratios of LC–MS–MS peaks

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