Spectral analysis of flow cytometric data : design of a special-purpose low-pass digital filter

Spectral decomposition of flow cytometric datafiles of arbitrary dimension reveal information of both the signal and the noise components that constitute the histograms. This spectral information is used to construct a low-pass digital filter, which removes the high-frequency noise from the actual d...

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Main Authors: Sloot, Peter M. A., Tensen, Pieter., Figdor, Carl G.
Other Authors: School of Computer Engineering
Format: Article
Language:English
Published: 2013
Subjects:
Online Access:https://hdl.handle.net/10356/96667
http://hdl.handle.net/10220/12105
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-966672020-05-28T07:19:13Z Spectral analysis of flow cytometric data : design of a special-purpose low-pass digital filter Sloot, Peter M. A. Tensen, Pieter. Figdor, Carl G. School of Computer Engineering DRNTU::Engineering::Computer science and engineering Spectral decomposition of flow cytometric datafiles of arbitrary dimension reveal information of both the signal and the noise components that constitute the histograms. This spectral information is used to construct a low-pass digital filter, which removes the high-frequency noise from the actual data. It is shown that this procedure guarantees non-trivial smoothing of the flow cytometric data in accordance with the local experimental situation. As a consequence optimal reconstruction of the signal is possible, which facilitates unambiguous interpretation of the data files and mathematical estimation of the statistical parameters. 2013-07-24T06:14:16Z 2019-12-06T19:33:43Z 2013-07-24T06:14:16Z 2019-12-06T19:33:43Z 1987 1987 Journal Article Sloot, P. M. A., Tensen, P., & Figdor, C. G. (1987). Spectral analysis of flow cytometric data: Design of a special-purpose low-pass digital filter. Cytometry, 8(6), 545-551. https://hdl.handle.net/10356/96667 http://hdl.handle.net/10220/12105 10.1002/cyto.990080603 en Cytometry © 1987 Alan It Liss, Inc.
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Sloot, Peter M. A.
Tensen, Pieter.
Figdor, Carl G.
Spectral analysis of flow cytometric data : design of a special-purpose low-pass digital filter
description Spectral decomposition of flow cytometric datafiles of arbitrary dimension reveal information of both the signal and the noise components that constitute the histograms. This spectral information is used to construct a low-pass digital filter, which removes the high-frequency noise from the actual data. It is shown that this procedure guarantees non-trivial smoothing of the flow cytometric data in accordance with the local experimental situation. As a consequence optimal reconstruction of the signal is possible, which facilitates unambiguous interpretation of the data files and mathematical estimation of the statistical parameters.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Sloot, Peter M. A.
Tensen, Pieter.
Figdor, Carl G.
format Article
author Sloot, Peter M. A.
Tensen, Pieter.
Figdor, Carl G.
author_sort Sloot, Peter M. A.
title Spectral analysis of flow cytometric data : design of a special-purpose low-pass digital filter
title_short Spectral analysis of flow cytometric data : design of a special-purpose low-pass digital filter
title_full Spectral analysis of flow cytometric data : design of a special-purpose low-pass digital filter
title_fullStr Spectral analysis of flow cytometric data : design of a special-purpose low-pass digital filter
title_full_unstemmed Spectral analysis of flow cytometric data : design of a special-purpose low-pass digital filter
title_sort spectral analysis of flow cytometric data : design of a special-purpose low-pass digital filter
publishDate 2013
url https://hdl.handle.net/10356/96667
http://hdl.handle.net/10220/12105
_version_ 1681059599455617024