Floptics: A novel automated gating technique for flow cytometry data
Floptics: A novel automated gating technique for flow cytometry data
Flow cytometry (FCM) determines the characteristics of individual biological cells using optical and fluorescence measurements. It is a widely used standard method for analysing blood samples in medical diagnostics, through identifying and quantifying the different types of cells in the samples. The multidimensional dataset obtained from FCM is large and complex, so it is difficult and time-consuming to analyse manually. The main process of differentiation and therefore labelling of the different cell populations in the data is referred to as Gating. This is the first step of FCM data analysis and is highly subjective, an issue that significant research has focussed on reducing. However, a faster standard gating technique is still needed. Existing automated gating techniques are time-consuming or retain subjectivity by requiring many user-defined parameters. This paper presents and discusses FLOPTICS: a novel automated gating technique that is a combination of density-based and grid-based clustering algorithms. FLOPTICS has an ability to classify and label cell populations in FCM data faster and with fewer user-defined parameters than many state-of-the-art techniques.
Flow cytometry, Automated gating, Density-based clustering
Sriphum, Wiwat
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Wills, Gary
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Green, Nicolas
d9b47269-c426-41fd-a41d-5f4579faa581
Sriphum, Wiwat
f9598d20-372e-48f4-9e41-99c23478141c
Wills, Gary
3a594558-6921-4e82-8098-38cd8d4e8aa0
Green, Nicolas
d9b47269-c426-41fd-a41d-5f4579faa581
Sriphum, Wiwat, Wills, Gary and Green, Nicolas
(2021)
Floptics: A novel automated gating technique for flow cytometry data.
International Journal of Organizational and Collective Intelligence, 12 (1).
Abstract
Flow cytometry (FCM) determines the characteristics of individual biological cells using optical and fluorescence measurements. It is a widely used standard method for analysing blood samples in medical diagnostics, through identifying and quantifying the different types of cells in the samples. The multidimensional dataset obtained from FCM is large and complex, so it is difficult and time-consuming to analyse manually. The main process of differentiation and therefore labelling of the different cell populations in the data is referred to as Gating. This is the first step of FCM data analysis and is highly subjective, an issue that significant research has focussed on reducing. However, a faster standard gating technique is still needed. Existing automated gating techniques are time-consuming or retain subjectivity by requiring many user-defined parameters. This paper presents and discusses FLOPTICS: a novel automated gating technique that is a combination of density-based and grid-based clustering algorithms. FLOPTICS has an ability to classify and label cell populations in FCM data faster and with fewer user-defined parameters than many state-of-the-art techniques.
Text
FlopticsRevised-eprints_wiwat
- Accepted Manuscript
More information
Accepted/In Press date: 24 September 2021
e-pub ahead of print date: 1 November 2021
Keywords:
Flow cytometry, Automated gating, Density-based clustering
Identifiers
Local EPrints ID: 468081
URI: http://eprints.soton.ac.uk/id/eprint/468081
ISSN: 1947-9344
PURE UUID: e0d3ed7e-016d-46b8-8aed-b38c2307f9b6
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Date deposited: 01 Aug 2022 16:52
Last modified: 17 Mar 2024 02:59
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Contributors
Author:
Wiwat Sriphum
Author:
Gary Wills
Author:
Nicolas Green
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