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Development of an Enhanced Total Ion Current Chromatogram Algorithm to Improve Untargeted Peak Detection

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journal contribution
posted on 29.07.2020, 15:09 by Caitlin N. Cain, Sonia Schöneich, Robert E. Synovec
Accurate analyte peak detection from the background noise is a fundamental step in data analysis. Often, this is initially performed on the total ion current chromatogram (TIC), which is the summed signal from all mass spectral channels. Despite the detection of many of the most abundant peaks within a chromatogram, a large fraction of peaks remains undetected in the standard TIC due to their signal being below the limit of detection. To find peaks obscured by background noise, an untargeted peak detection method termed the “enhanced TIC algorithm” was developed for comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOFMS). The reported algorithm utilizes the entire mass spectral dimension to find regions of analytical signal above a threshold while zeroing the background noise. The resulting chromatographic data is summed together to create the enhanced TIC. The utility of the enhanced TIC algorithm is demonstrated using serial dilutions from a 10 parts-per-thousand (ppth) test mixture. For the chromatograms collected at 1 and 10 parts-per-million (ppm), the enhanced TIC algorithm recovered 62% and 93%, respectively, of the original peaks observed in the 10 ppth mixture, while the standard TIC recovered only 0% and 45%, respectively. The improvement in signal enhancement was also shown on a separation of a yeast cell metabolite extract, where the enhanced TIC found 33–64% more peaks than the standard TIC. Chromatographic simulations with increasing levels of background noise were also conducted to compare the enhanced and standard TICs in the context of statistical overlap theory (SOT). Simulated chromatograms with lower signal-to-noise were more accurately modeled by the SOT after enhanced TIC processing compared to those processed by the standard TIC. The enhanced TIC method demonstrates an immense benefit in peak discovery to improve data analysis efforts.

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