Emily A Gordon, David L Bennett, Georgios Baskozos, Maddalena Comini
{"title":"MEAanalysis: an open-source R package for downstream visualization of AxIS navigator multi-electrode array burst data at the single-electrode level.","authors":"Emily A Gordon, David L Bennett, Georgios Baskozos, Maddalena Comini","doi":"10.1093/bioadv/vbaf160","DOIUrl":null,"url":null,"abstract":"<p><strong>Summary: </strong>Multi-electrode array (MEA) generate electrophysiological data that can be used to functionally characterize excitable cells. MEA data can be complex to analyse in a reproducible manner, with current data analysis tools often calculating parameters at the whole-well level. Here we present MEAanalysis, an open-source R package [GPL (≥2)] able to visualize burst parameters at the single electrode level downstream of AxIS Navigator software (Axion BioSystems) processing, thus increasing our understanding of an excitable cell network's spatiotemporal variability.</p><p><strong>Availability and implementation: </strong>The package is hosted on and can be installed from the following GitHub repository: https://github.com/egordon2/MEA-analysis-package. User feedback provided via email or the GitHub issues tab will inform cycles of development.</p>","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"5 1","pages":"vbaf160"},"PeriodicalIF":2.8000,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12311347/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics advances","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioadv/vbaf160","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Summary: Multi-electrode array (MEA) generate electrophysiological data that can be used to functionally characterize excitable cells. MEA data can be complex to analyse in a reproducible manner, with current data analysis tools often calculating parameters at the whole-well level. Here we present MEAanalysis, an open-source R package [GPL (≥2)] able to visualize burst parameters at the single electrode level downstream of AxIS Navigator software (Axion BioSystems) processing, thus increasing our understanding of an excitable cell network's spatiotemporal variability.
Availability and implementation: The package is hosted on and can be installed from the following GitHub repository: https://github.com/egordon2/MEA-analysis-package. User feedback provided via email or the GitHub issues tab will inform cycles of development.