XFlow: An algorithm for extracting ion chromatograms

• Published in: PloS one Vol. 15; no. 10; p. e0227659
• Main Authors: Gutierrez, Mathew, Smith, Rob
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 22.10.2020; Public Library of Science (PLoS)
• Subjects: Algorithms; Analytical methods; Chromatography; Chromatography, Liquid; Clustering; Computational Biology - methods; Computer and Information Sciences; Computer science; Datasets; Engineering and Technology; Feature extraction; Hypotheses; Ions - analysis; Mass spectrometry; Mass spectroscopy; Physical Sciences; Proteomics; Proteomics - methods; Research and Analysis Methods; Science Policy; Scientific imaging; Source code; Spectroscopy; Tandem Mass Spectrometry; Target acquisition; Technology application; Toolkits; United States; United States > US
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0227659

Mass spectrometry is a fundamental tool for modern proteomics. The increasing availability of mass spectrometry data paired with the increasing sensitivity and fidelity of the instruments necessitates new and more potent analytical methods. To that end, we have created and present XFlow, a feature detection algorithm for extracting ion chromatograms from MS1 LC-MS data. XFlow is a parameter-free procedurally agnostic feature detection algorithm that utilizes the latent properties of ion chromatograms to resolve them from the surrounding noise present in MS1 data. XFlow is designed to function on either profile or centroided data across different resolutions and instruments. This broad applicability lends XFlow strong utility as a one-size-fits-all method for MS1 analysis or target acquisition for MS2. XFlow is written in Java and packaged with JS-MS, an open-source mass spectrometry analysis toolkit.