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Title: ECHO: an application for detection and analysis of oscillators identifies metabolic regulation on genome-wide circadian output

Abstract

Abstract Motivation Time courses utilizing genome scale data are a common approach to identifying the biological pathways that are controlled by the circadian clock, an important regulator of organismal fitness. However, the methods used to detect circadian oscillations in these datasets are not able to accommodate changes in the amplitude of the oscillations over time, leading to an underestimation of the impact of the clock on biological systems. Results We have created a program to efficaciously identify oscillations in large-scale datasets, called the Extended Circadian Harmonic Oscillator application, or ECHO. ECHO utilizes an extended solution of the fixed amplitude oscillator that incorporates the amplitude change coefficient. Employing synthetic datasets, we determined that ECHO outperforms existing methods in detecting rhythms with decreasing oscillation amplitudes and in recovering phase shift. Rhythms with changing amplitudes identified from published biological datasets revealed distinct functions from those oscillations that were harmonic, suggesting purposeful biologic regulation to create this subtype of circadian rhythms. Availability and implementation ECHO’s full interface is available at https://github.com/delosh653/ECHO. An R package for this functionality, echo.find, can be downloaded at https://CRAN.R-project.org/package=echo.find. Supplementary information Supplementary data are available at Bioinformatics online.

Authors:
 [1];  [2];  [2];  [3];  [2];  [4];  [5];
  1. Department of Computer Science, Troy, NY 12180, USA, Institute for Data Exploration and Applications, Troy, NY 12180, USA
  2. Department of Biological Sciences, Troy, NY 12180, USA
  3. Department of Mathematical Sciences, Troy, NY 12180, USA
  4. Department of Computer Science, Troy, NY 12180, USA, Institute for Data Exploration and Applications, Troy, NY 12180, USA, Department of Mathematical Sciences, Troy, NY 12180, USA
  5. Department of Biological Sciences, Troy, NY 12180, USA, Center for Biotechnology and Interdisciplinary Sciences, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1646506
Grant/Contract Number:  
PNNL 47818
Resource Type:
Published Article
Journal Name:
Bioinformatics
Additional Journal Information:
Journal Name: Bioinformatics Journal Volume: 36 Journal Issue: 3; Journal ID: ISSN 1367-4803
Publisher:
Oxford University Press
Country of Publication:
United Kingdom
Language:
English

Citation Formats

De los Santos, Hannah, Collins, Emily J., Mann, Catherine, Sagan, April W., Jankowski, Meaghan S., Bennett, Kristin P., Hurley, Jennifer M., and Kelso, ed., Janet. ECHO: an application for detection and analysis of oscillators identifies metabolic regulation on genome-wide circadian output. United Kingdom: N. p., 2019. Web. https://doi.org/10.1093/bioinformatics/btz617.
De los Santos, Hannah, Collins, Emily J., Mann, Catherine, Sagan, April W., Jankowski, Meaghan S., Bennett, Kristin P., Hurley, Jennifer M., & Kelso, ed., Janet. ECHO: an application for detection and analysis of oscillators identifies metabolic regulation on genome-wide circadian output. United Kingdom. https://doi.org/10.1093/bioinformatics/btz617
De los Santos, Hannah, Collins, Emily J., Mann, Catherine, Sagan, April W., Jankowski, Meaghan S., Bennett, Kristin P., Hurley, Jennifer M., and Kelso, ed., Janet. Tue . "ECHO: an application for detection and analysis of oscillators identifies metabolic regulation on genome-wide circadian output". United Kingdom. https://doi.org/10.1093/bioinformatics/btz617.
@article{osti_1646506,
title = {ECHO: an application for detection and analysis of oscillators identifies metabolic regulation on genome-wide circadian output},
author = {De los Santos, Hannah and Collins, Emily J. and Mann, Catherine and Sagan, April W. and Jankowski, Meaghan S. and Bennett, Kristin P. and Hurley, Jennifer M. and Kelso, ed., Janet},
abstractNote = {Abstract Motivation Time courses utilizing genome scale data are a common approach to identifying the biological pathways that are controlled by the circadian clock, an important regulator of organismal fitness. However, the methods used to detect circadian oscillations in these datasets are not able to accommodate changes in the amplitude of the oscillations over time, leading to an underestimation of the impact of the clock on biological systems. Results We have created a program to efficaciously identify oscillations in large-scale datasets, called the Extended Circadian Harmonic Oscillator application, or ECHO. ECHO utilizes an extended solution of the fixed amplitude oscillator that incorporates the amplitude change coefficient. Employing synthetic datasets, we determined that ECHO outperforms existing methods in detecting rhythms with decreasing oscillation amplitudes and in recovering phase shift. Rhythms with changing amplitudes identified from published biological datasets revealed distinct functions from those oscillations that were harmonic, suggesting purposeful biologic regulation to create this subtype of circadian rhythms. Availability and implementation ECHO’s full interface is available at https://github.com/delosh653/ECHO. An R package for this functionality, echo.find, can be downloaded at https://CRAN.R-project.org/package=echo.find. Supplementary information Supplementary data are available at Bioinformatics online.},
doi = {10.1093/bioinformatics/btz617},
journal = {Bioinformatics},
number = 3,
volume = 36,
place = {United Kingdom},
year = {2019},
month = {8}
}

Journal Article:
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https://doi.org/10.1093/bioinformatics/btz617

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