XFlow: An algorithm for extracting ion chromatograms

Author

Mathew M. Gutierrez, University of Montana, MissoulaFollow
Rob Smith, University of Montana, MissoulaFollow

Year of Award

2019

Document Type

Thesis

Degree Type

Master of Science (MS)

Degree Name

Computer Science

Department or School/College

Computer Science

Committee Chair

Rob Smith

Commitee Members

Rob Smith, Travis Wheeler, Chris Palmer

Keywords

mass spectrometry, proteomics, annotation, segmentation

Subject Categories

Analytical Chemistry | Medicinal and Pharmaceutical Chemistry | Medicinal-Pharmaceutical Chemistry

Abstract

Abstract: 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.

Recommended Citation

Gutierrez, Mathew M. and Smith, Rob, "XFlow: An algorithm for extracting ion chromatograms" (2019). Graduate Student Theses, Dissertations, & Professional Papers. 11491.
https://scholarworks.umt.edu/etd/11491