2013
DOI: 10.1039/c3an36276k
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An automated method for baseline correction, peak finding and peak grouping in chromatographic data

Abstract: An automated method (FastChrom) for baseline correction, peak detection and assignment (grouping) of similar peaks across samples has been developed. The method has been tested both on artificial data and a dataset obtained from gas chromatograph analysis of wine samples. As part of the automated approach, a new method for baseline estimation has been developed and compared with other methods. FastChrom has been shown to perform at least as well as conventional software. However, compared to other approaches, … Show more

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Cited by 20 publications
(9 citation statements)
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“…However, due to the different algorithms implemented in these programs, they might produce different and even contradictory results [ 23 ]. Multiple studies have evaluated and compared different data processing and identification algorithms used in these programs [ 52 57 ]. We found that the PEAKS program identified and mapped considerably higher number of peptides compared to the other programs.…”
Section: Discussionmentioning
confidence: 99%
“…However, due to the different algorithms implemented in these programs, they might produce different and even contradictory results [ 23 ]. Multiple studies have evaluated and compared different data processing and identification algorithms used in these programs [ 52 57 ]. We found that the PEAKS program identified and mapped considerably higher number of peptides compared to the other programs.…”
Section: Discussionmentioning
confidence: 99%
“…Chromatographic data were handled within a data set. Chromatographic profiles monitored at 270 nm as function of time (baselinecorrected using FastChrom algorithm, (Johnsen et al, 2013)) were exported as 2D ASCII files for each sample and a matrix of 1502 x 25 points was then built. Twoway array raw data were submitted to chromatographic peak alignment as first step of pretreatment prior to the statistical analysis.…”
Section: Discussionmentioning
confidence: 99%
“…This has been implemented and validated for use in data from systems like HPLC-DAD 23 . Baseline estimation was built on the Asymmetric Least Squares 23 , a method in which a second derivative constrained weighted regression algorithm is used for baseline correction. This was performed using a second derivative constraint of 10, a weighting of positive residuals parameter of 0.01, and a maximum of 20 iterations.…”
Section: Methodsmentioning
confidence: 99%