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WAVOS: a MATLAB toolkit for wavelet analysis and visualization of oscillatory systems

BACKGROUND: Wavelets have proven to be a powerful technique for the analysis of periodic data, such as those that arise in the analysis of circadian oscillators. While many implementations of both continuous and discrete wavelet transforms are available, we are aware of no software that has been des...

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Autores principales: Harang, Richard, Bonnet, Guillaume, Petzold, Linda R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3353168/
https://www.ncbi.nlm.nih.gov/pubmed/22448897
http://dx.doi.org/10.1186/1756-0500-5-163
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author Harang, Richard
Bonnet, Guillaume
Petzold, Linda R
author_facet Harang, Richard
Bonnet, Guillaume
Petzold, Linda R
author_sort Harang, Richard
collection PubMed
description BACKGROUND: Wavelets have proven to be a powerful technique for the analysis of periodic data, such as those that arise in the analysis of circadian oscillators. While many implementations of both continuous and discrete wavelet transforms are available, we are aware of no software that has been designed with the nontechnical end-user in mind. By developing a toolkit that makes these analyses accessible to end users without significant programming experience, we hope to promote the more widespread use of wavelet analysis. FINDINGS: We have developed the WAVOS toolkit for wavelet analysis and visualization of oscillatory systems. WAVOS features both the continuous (Morlet) and discrete (Daubechies) wavelet transforms, with a simple, user-friendly graphical user interface within MATLAB. The interface allows for data to be imported from a number of standard file formats, visualized, processed and analyzed, and exported without use of the command line. Our work has been motivated by the challenges of circadian data, thus default settings appropriate to the analysis of such data have been pre-selected in order to minimize the need for fine-tuning. The toolkit is flexible enough to deal with a wide range of oscillatory signals, however, and may be used in more general contexts. CONCLUSIONS: We have presented WAVOS: a comprehensive wavelet-based MATLAB toolkit that allows for easy visualization, exploration, and analysis of oscillatory data. WAVOS includes both the Morlet continuous wavelet transform and the Daubechies discrete wavelet transform. We have illustrated the use of WAVOS, and demonstrated its utility for the analysis of circadian data on both bioluminesence and wheel-running data. WAVOS is freely available at http://sourceforge.net/projects/wavos/files/
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spelling pubmed-33531682012-05-16 WAVOS: a MATLAB toolkit for wavelet analysis and visualization of oscillatory systems Harang, Richard Bonnet, Guillaume Petzold, Linda R BMC Res Notes Technical Note BACKGROUND: Wavelets have proven to be a powerful technique for the analysis of periodic data, such as those that arise in the analysis of circadian oscillators. While many implementations of both continuous and discrete wavelet transforms are available, we are aware of no software that has been designed with the nontechnical end-user in mind. By developing a toolkit that makes these analyses accessible to end users without significant programming experience, we hope to promote the more widespread use of wavelet analysis. FINDINGS: We have developed the WAVOS toolkit for wavelet analysis and visualization of oscillatory systems. WAVOS features both the continuous (Morlet) and discrete (Daubechies) wavelet transforms, with a simple, user-friendly graphical user interface within MATLAB. The interface allows for data to be imported from a number of standard file formats, visualized, processed and analyzed, and exported without use of the command line. Our work has been motivated by the challenges of circadian data, thus default settings appropriate to the analysis of such data have been pre-selected in order to minimize the need for fine-tuning. The toolkit is flexible enough to deal with a wide range of oscillatory signals, however, and may be used in more general contexts. CONCLUSIONS: We have presented WAVOS: a comprehensive wavelet-based MATLAB toolkit that allows for easy visualization, exploration, and analysis of oscillatory data. WAVOS includes both the Morlet continuous wavelet transform and the Daubechies discrete wavelet transform. We have illustrated the use of WAVOS, and demonstrated its utility for the analysis of circadian data on both bioluminesence and wheel-running data. WAVOS is freely available at http://sourceforge.net/projects/wavos/files/ BioMed Central 2012-03-26 /pmc/articles/PMC3353168/ /pubmed/22448897 http://dx.doi.org/10.1186/1756-0500-5-163 Text en Copyright ©2012 Harang et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Technical Note
Harang, Richard
Bonnet, Guillaume
Petzold, Linda R
WAVOS: a MATLAB toolkit for wavelet analysis and visualization of oscillatory systems
title WAVOS: a MATLAB toolkit for wavelet analysis and visualization of oscillatory systems
title_full WAVOS: a MATLAB toolkit for wavelet analysis and visualization of oscillatory systems
title_fullStr WAVOS: a MATLAB toolkit for wavelet analysis and visualization of oscillatory systems
title_full_unstemmed WAVOS: a MATLAB toolkit for wavelet analysis and visualization of oscillatory systems
title_short WAVOS: a MATLAB toolkit for wavelet analysis and visualization of oscillatory systems
title_sort wavos: a matlab toolkit for wavelet analysis and visualization of oscillatory systems
topic Technical Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3353168/
https://www.ncbi.nlm.nih.gov/pubmed/22448897
http://dx.doi.org/10.1186/1756-0500-5-163
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