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

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 DQSpeak, rendering low reliability results more transparent
during processing and allowing for the prioritization of generated
features. High DQSpeak 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.