ArticleBMC bioinformatics2015
plethy: management of whole body plethysmography data in R.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundCharacterization of respiratory phenotypes can enhance complex trait and genomic studies involving allergic/autoimmune and infectious diseases. Many aspects of respiration can be measured using devices known as plethysmographs that can measure thoracic movement. One such approach (the Buxco platform) performs unrestrained whole body plethysmography on mice which infers thoracic movements from pressure differences from the act of inhalation and exhalation. While proprietary software is available to perform basic statistical analysis as part of machine's bundled software, it is desirable to be able to incorporate these analyses into high-throughput pipelines and integrate them with other data types, as well as leverage the wealth of analytic and visualization approaches provided by the R statistical computing environment.
resultsThis manuscript describes the plethy package which is an R/Bioconductor framework for pre-processing and analysis of plethysmography data with emphasis on larger scale longitudinal experiments. The plethy package was designed to facilitate quality control and exploratory data analysis. We provide a demonstration of the features of plethy using a dataset assessing the respiratory effects over time of SARS and Influenza infection in mice.
conclusionThe plethy package provides functionality for users to import, perform quality assessment and exploratory data analysis in a manner that allows interoperability with existing modelling tools. Our package is implemented in R and is freely available as part of the Bioconductor project http://www.bioconductor.org/packages/release/bioc/html/plethy.html .
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