An automated respiratory data pipeline for waveform characteristic analysis

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dc.citation.firstpage4767en_US
dc.citation.issueNumber21en_US
dc.citation.journalTitleThe Journal of Physiologyen_US
dc.citation.lastpage4806en_US
dc.citation.volumeNumber601en_US
dc.contributor.authorLusk, Savannahen_US
dc.contributor.authorWard, Christopher S.en_US
dc.contributor.authorChang, Andersenen_US
dc.contributor.authorTwitchell-Heyne, Averyen_US
dc.contributor.authorFattig, Shaunen_US
dc.contributor.authorAllen, Geneveraen_US
dc.contributor.authorJankowsky, Joanna L.en_US
dc.contributor.authorRay, Russell S.en_US
dc.date.accessioned2024-05-08T18:56:10Zen_US
dc.date.available2024-05-08T18:56:10Zen_US
dc.date.issued2023en_US
dc.description.abstractComprehensive and accurate analysis of respiratory and metabolic data is crucial to modelling congenital, pathogenic and degenerative diseases converging on autonomic control failure. A lack of tools for high-throughput analysis of respiratory datasets remains a major challenge. We present Breathe Easy, a novel open-source pipeline for processing raw recordings and associated metadata into operative outcomes, publication-worthy graphs and robust statistical analyses including QQ and residual plots for assumption queries and data transformations. This pipeline uses a facile graphical user interface for uploading data files, setting waveform feature thresholds and defining experimental variables. Breathe Easy was validated against manual selection by experts, which represents the current standard in the field. We demonstrate Breathe Easy's utility by examining a 2-year longitudinal study of an Alzheimer's disease mouse model to assess contributions of forebrain pathology in disordered breathing. Whole body plethysmography has become an important experimental outcome measure for a variety of diseases with primary and secondary respiratory indications. Respiratory dysfunction, while not an initial symptom in many of these disorders, often drives disability or death in patient outcomes. Breathe Easy provides an open-source respiratory analysis tool for all respiratory datasets and represents a necessary improvement upon current analytical methods in the field. Key points Respiratory dysfunction is a common endpoint for disability and mortality in many disorders throughout life. Whole body plethysmography in rodents represents a high face-value method for measuring respiratory outcomes in rodent models of these diseases and disorders. Analysis of key respiratory variables remains hindered by manual annotation and analysis that leads to low throughput results that often exclude a majority of the recorded data. Here we present a software suite, Breathe Easy, that automates the process of data selection from raw recordings derived from plethysmography experiments and the analysis of these data into operative outcomes and publication-worthy graphs with statistics. We validate Breathe Easy with a terabyte-scale Alzheimer's dataset that examines the effects of forebrain pathology on respiratory function over 2 years of degeneration.en_US
dc.identifier.citationLusk, S., Ward, C. S., Chang, A., Twitchell-Heyne, A., Fattig, S., Allen, G., Jankowsky, J. L., & Ray, R. S. (2023). An automated respiratory data pipeline for waveform characteristic analysis. The Journal of Physiology, 601(21), 4767–4806. https://doi.org/10.1113/JP284363en_US
dc.identifier.digitalAn-automated-respiratory-data-pipelineen_US
dc.identifier.doihttps://doi.org/10.1113/JP284363en_US
dc.identifier.urihttps://hdl.handle.net/1911/115673en_US
dc.language.isoengen_US
dc.publisherWileyen_US
dc.rightsExcept where otherwise noted, this work is licensed under a Creative Commons Attribution-NonCommercial (CC BY-NC) license. Permission to reuse, publish, or reproduce the work beyond the terms of the license or beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/en_US
dc.titleAn automated respiratory data pipeline for waveform characteristic analysisen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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