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Title: meaRtools: An R package for the analysis of neuronal networks recorded on microelectrode arrays.
Austin Authors: Gelfman, Sahar;Wang, Quanli;Lu, Yi-Fan;Hall, Diana;Bostick, Christopher D;Dhindsa, Ryan;Halvorsen, Matt;McSweeney, K Melodi;Cotterill, Ellese;Edinburgh, Tom;Beaumont, Michael A;Frankel, Wayne N;Petrovski, Slavé;Allen, Andrew S;Boland, Michael J;Goldstein, David B;Eglen, Stephen J
Affiliation: Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia
Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, Victoria, Australia
Cambridge Computational Biology Institute, University of Cambridge, Cambridge, United Kingdom
Department of Genetics and Development, Columbia University Medical Center, New York, NY, United States of America
Simcere Diagnostics Co, Ltd, Nanjing, China
Department of Biology, Westmont College, Santa Barbara, CA, United States of America
Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
University Program in Genetics and Genomics, Duke University, Durham, North Carolina, United States of America
Axion BioSystems, Inc., Atlanta, GA, United States of America
Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, United States of America
Department of Neurology, Columbia University, New York, NY, United States of America
Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, United States of America
Issue Date: Oct-2018 2018-10-01
Publication information: PLoS computational biology 2018; 14(10): e1006506
Abstract: Here we present an open-source R package 'meaRtools' that provides a platform for analyzing neuronal networks recorded on Microelectrode Arrays (MEAs). Cultured neuronal networks monitored with MEAs are now being widely used to characterize in vitro models of neurological disorders and to evaluate pharmaceutical compounds. meaRtools provides core algorithms for MEA spike train analysis, feature extraction, statistical analysis and plotting of multiple MEA recordings with multiple genotypes and treatments. meaRtools functionality covers novel solutions for spike train analysis, including algorithms to assess electrode cross-correlation using the spike train tiling coefficient (STTC), mutual information, synchronized bursts and entropy within cultured wells. Also integrated is a solution to account for bursts variability originating from mixed-cell neuronal cultures. The package provides a statistical platform built specifically for MEA data that can combine multiple MEA recordings and compare extracted features between different genetic models or treatments. We demonstrate the utilization of meaRtools to successfully identify epilepsy-like phenotypes in neuronal networks from Celf4 knockout mice. The package is freely available under the GPL license (GPL> = 3) and is updated frequently on the CRAN web-server repository. The package, along with full documentation can be downloaded from:
DOI: 10.1371/journal.pcbi.1006506
ORCID: 0000-0002-4727-7862
Journal: PLoS computational biology
PubMed URL: 30273353
Type: Journal Article
Appears in Collections:Journal articles

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