Gang Wu1, Ron C Anafi2, Michael E Hughes3, Karl Kornacker4, John B Hogenesch1. 1. Department of Systems Pharmacology and Translational Therapeutics, Institute for Translational Medicine and Therapeutics. 2. Division of Sleep Medicine Center for Sleep and Circadian Neurobiology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA. 3. Department of Biology, University of Missouri-St. Louis, St. Louis, MO 63121, USA. 4. Emeritus Professor of Sensory Biophysics, the Ohio State University, Columbus, OH 43210, USA.
Abstract
Detecting periodicity in large scale data remains a challenge. While efforts have been made to identify best of breed algorithms, relatively little research has gone into integrating these methods in a generalizable method. Here, we present MetaCycle, an R package that incorporates ARSER, JTK_CYCLE and Lomb-Scargle to conveniently evaluate periodicity in time-series data. MetaCycle has two functions, meta2d and meta3d, designed to analyze two-dimensional and three-dimensional time-series datasets, respectively. Meta2d implements N-version programming concepts using a suite of algorithms and integrating their results. AVAILABILITY AND IMPLEMENTATION: MetaCycle package is available on the CRAN repository (https://cran.r-project.org/web/packages/MetaCycle/index.html) and GitHub (https://github.com/gangwug/MetaCycle). CONTACT: hogenesch@gmail.comSupplementary information: Supplementary data are available at Bioinformatics online.
Detecting periodicity in large scale data remains a challenge. While efforts have been made to identify best of breed algorithms, relatively little research has gone into integrating these methods in a generalizable method. Here, we present MetaCycle, an R package that incorporates ARSER, JTK_CYCLE and Lomb-Scargle to conveniently evaluate periodicity in time-series data. MetaCycle has two functions, meta2d and meta3d, designed to analyze two-dimensional and three-dimensional time-series datasets, respectively. Meta2d implements N-version programming concepts using a suite of algorithms and integrating their results. AVAILABILITY AND IMPLEMENTATION: MetaCycle package is available on the CRAN repository (https://cran.r-project.org/web/packages/MetaCycle/index.html) and GitHub (https://github.com/gangwug/MetaCycle). CONTACT: hogenesch@gmail.comSupplementary information: Supplementary data are available at Bioinformatics online.
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