qPeaks: A Linear Regression-Based Asymmetric Peak Model for Parameter-Free Automatized Detection and Characterization of Chromatographic Peaks in Non-Target Screening Data,Analytical Chemistry

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qPeaks: A Linear Regression-Based Asymmetric Peak Model for Parameter-Free Automatized Detection and Characterization of Chromatographic Peaks in Non-Target Screening Data
Analytical Chemistry ( IF 6.7 ) Pub Date : 2024-04-26 , DOI: 10.1021/acs.analchem.4c00494
Max Reuschenbach _{1,

2} , Felix Drees _{1,

2} , Michael S Leupold _{1,

2} , Lucie K Tintrop _{1,

2} , Torsten C Schmidt _{1,

2,

3} , Gerrit Renner _{1,

2}

Affiliation

We present qPeaks (quality peaks), a novel, user-parameter-free algorithm for peak detection and peak characterization applicable to chromatographic data. The algorithm is based on a linearizable regression model that analyzes asymmetric peaks and estimates the specific uncertainties associated with the peak regression parameters. The uncertainties of the parameters are used to derive a data quality score DQS_peak, rendering low reliability results more transparent during processing and allowing for the prioritization of generated features. High DQS_peak chromatographic peaks have a lower chance of being classified as false-positive and show higher repeatability over multiple measurements. The high efficiency of the algorithm makes it particularly useful for application within processing routines of nontarget screening through chromatography coupled with high-resolution mass spectrometry. qPeaks is integrated into the qAlgorithms nontarget screening processing toolbox and appends a parameter-free chromatographic peak detection and characterization step to it. With qAlgorithms, now high-resolution mass spectra are centroided using the qCentroids algorithms, centroids are clustered to form extracted ion chromatograms (EICs) with the qBinning algorithm, and chromatographic peaks are found on the generated EICs with qPeaks. However, all tools from qAlgorithms can also be used independently.

中文翻译：

qPeaks：基于线性回归的不对称峰模型，用于非目标筛选数据中色谱峰的无参数自动检测和表征

我们推出了 qPeaks（质量峰），这是一种新颖的、无用户参数的算法，用于适用于色谱数据的峰检测和峰表征。该算法基于线性回归模型，该模型分析不对称峰并估计与峰回归参数相关的特定不确定性。参数的不确定性用于导出数据质量得分 DQS _Peak ，使低可靠性结果在处理过程中更加透明，并允许对生成的特征进行优先级排序。高 DQS_峰色谱峰被分类为假阳性的可能性较低，并且在多次测量中显示出较高的重复性。该算法的高效率使其特别适用于通过色谱法与高分辨率质谱法进行非目标筛选的处理例程。 qPeaks 集成到 qAlgorithms 非目标筛选处理工具箱中，并附加了无参数色谱峰检测和表征步骤。借助 qAlgorithms，现在使用 qCentroids 算法对高分辨率质谱进行质心处理，使用 qBinning 算法对质心进行聚类以形成提取离子色谱图 (EIC)，并使用 qPeaks 在生成的 EIC 上找到色谱峰。然而，qAlgorithms 的所有工具也可以独立使用。

更新日期：2024-04-26

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