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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/24162

Title: Computational quality control tools for mass spectrometry proteomics
Authors: Bittremieux, Wout
Valkenborg, Dirk
Martens, Lennart
Laukens, Kris
Issue Date: 2017
Publisher: WILEY
Citation: PROTEOMICS, 17(3-4), p. 1-11 (Art N° 1600159)
Abstract: As mass-spectrometry-based proteomics has matured during the past decade, a growing emphasis has been placed on quality control. For this purpose, multiple computational quality control tools have been introduced. These tools generate a set of metrics that can be used to assess the quality of a mass spectrometry experiment. Here we review which types of quality control metrics can be generated, and how they can be used to monitor both intra-and inter-experiment performances. We discuss the principal computational tools for quality control and list their main characteristics and applicability. Asmost of these tools have specific use cases, it is not straightforward to compare their performances. For this survey, we used different sets of quality control metrics derived from information at various stages in a mass spectrometry process and evaluated their effectiveness at capturing qualitative information about an experiment using a supervised learning approach. Furthermore, we discuss currently available algorithmic solutions that enable the usage of these quality control metrics for decision-making.
Notes: [Bittremieux, Wout; Laukens, Kris] Univ Antwerp, Dept Math & Comp Sci, Antwerp, Belgium. [Bittremieux, Wout; Laukens, Kris] Univ Antwerp, Univ Hosp, Biomed Informat Res Ctr Antwerp Biomina, Edegem, Belgium. [Valkenborg, Dirk] Flemish Inst Technol Res VITO, Mol, Belgium. [Valkenborg, Dirk] Univ Antwerp, CFP, Antwerp, Belgium. [Valkenborg, Dirk] Hasselt Univ, I BioStat, Diepenbeek, Belgium. [Martens, Lennart] VIB, Ctr Med Biotechnol, Ghent, Belgium. [Martens, Lennart] Univ Ghent, Fac Med & Hlth Sci, Dept Biochem, Ghent, Belgium. [Martens, Lennart] Univ Ghent, Bioinformat Inst Ghent, Zwijnaarde, Belgium.
URI: http://hdl.handle.net/1942/24162
DOI: 10.1002/pmic.201600159
ISI #: 000397012800005
ISSN: 1615-9853
Category: A1
Type: Journal Contribution
Validation: ecoom, 2018
Appears in Collections: Research publications

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