The University of Southampton
University of Southampton Institutional Repository

FLOPTICS: A novel automated gating technique for flow cytometry data

FLOPTICS: A novel automated gating technique for flow cytometry data
FLOPTICS: A novel automated gating technique for flow cytometry data

Flow cytometry (FCM) involves the use of optical and fluorescence measurements of the characteristics of individual biological cells, typically in blood samples. It is a widely used standard method of analysing blood samples for the purpose of identifying and quantifying the different types of cells in the sample, the result of which are used in medical diagnoses. 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 populations in the data which represent types of cells is referred to as Gating: Gating is the first step of FCM data analysis and highly subjective. Significant amounts of research have focussed on reducing this subjectivity, however a faster standard gating technique is still needed. Existing automated gating techniques are time-consuming or need many user-defined parameters which affect the differentiation to different clustering results. 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 cells on FCM data faster and with fewer user-defined parameters than many state-of-the-art techniques, such as FlowGrid, FlowPeaks, and FLOCK.

automated gating, density based clustering, flow cytometry, optics clustering
96-102
Sriphum, Wiwat
f9598d20-372e-48f4-9e41-99c23478141c
Wills, Gary
3a594558-6921-4e82-8098-38cd8d4e8aa0
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 (2020) FLOPTICS: A novel automated gating technique for flow cytometry data. 5th International Conference on Complexity, Future Information Systems and Risk, Vienna House Diplomat Prague Evropska 15 16041 Prague, Czech Republic, Prague, Czech Republic. 08 - 09 May 2020. pp. 96-102 .

Record type: Conference or Workshop Item (Paper)

Abstract

Flow cytometry (FCM) involves the use of optical and fluorescence measurements of the characteristics of individual biological cells, typically in blood samples. It is a widely used standard method of analysing blood samples for the purpose of identifying and quantifying the different types of cells in the sample, the result of which are used in medical diagnoses. 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 populations in the data which represent types of cells is referred to as Gating: Gating is the first step of FCM data analysis and highly subjective. Significant amounts of research have focussed on reducing this subjectivity, however a faster standard gating technique is still needed. Existing automated gating techniques are time-consuming or need many user-defined parameters which affect the differentiation to different clustering results. 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 cells on FCM data faster and with fewer user-defined parameters than many state-of-the-art techniques, such as FlowGrid, FlowPeaks, and FLOCK.

Text
ws5n17_COMPLEXIS_2020 - Author's Original
Download (671kB)

More information

Submitted date: 7 January 2020
Published date: 8 May 2020
Additional Information: Publisher Copyright: © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
Venue - Dates: 5th International Conference on Complexity, Future Information Systems and Risk, Vienna House Diplomat Prague Evropska 15 16041 Prague, Czech Republic, Prague, Czech Republic, 2020-05-08 - 2020-05-09
Keywords: automated gating, density based clustering, flow cytometry, optics clustering

Identifiers

Local EPrints ID: 440966
URI: http://eprints.soton.ac.uk/id/eprint/440966
PURE UUID: 79b71b71-1d68-4808-9734-ce576f0d2137
ORCID for Gary Wills: ORCID iD orcid.org/0000-0001-5771-4088
ORCID for Nicolas Green: ORCID iD orcid.org/0000-0001-9230-4455

Catalogue record

Date deposited: 26 May 2020 16:31
Last modified: 03 Aug 2022 01:39

Export record

Contributors

Author: Wiwat Sriphum
Author: Gary Wills ORCID iD
Author: Nicolas Green ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×