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

机译:开发增强的总离子电流色谱图算法,以改善未确定的峰值检测

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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 X 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.
机译:从背景噪声中精确分析物峰值检测是数据分析的基本步骤。通常,这最初在总离子电流色谱图(TIC)上执行,其是来自所有质谱通道的总和信号。尽管在色谱图中检测到许多最丰富的峰值,但由于其信号低于检测极限,因此在标准TIC中,大部分峰值保持未被发现。为了发现通过背景噪声模糊的峰值,为具有飞行时间质谱(GC X GC-TOFMS)耦合的综合二维气相色谱(GC X GC-TOFM),开发了称为“增强的TIC算法”的未确定峰值检测方法。报告的算法利用整个质谱尺寸来查找在阈值高于阈值的分析信号区域,同时归零背景噪声。得到的色谱数据总结在一起以产生增强的TIC。使用10份每千(PPTH)测试混合物的连续稀释液来证明增强的TIC算法的效用。对于在每百万份(PPM)以1和10分份收集的色谱图,增强的TIC算法分别回收了62%和93%,在10个PPTH混合物中观察到的原始峰,而标准TIC仅回收0%和分别为45%。在酵母细胞代谢物提取物的分离上也显示出信号增强的改善,其中增强的TIC比标准TIC更高的峰。还进行了随着越来越多的背景噪声水平的色谱模拟,以比较统计重叠理论(SOT)背景下的增强和标准抽题。与由标准TIC处理的那些相比,在增强的TIC处理后,SOT更精确地模拟了具有较低信噪比的模拟色谱图。增强的TIC方法证明了峰值发现中的巨大益处,以改善数据分析工作。

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