This package is under active development, but is currently stable.
respR is an R package that provides a structural, reproducible workflow for the processing and analysis of respirometry data.
While the focus of our package is on aquatic respirometry,
respR is largely unitless and so can process linear relationships in any time-series data, such as oxygen flux or photosynthesis.
Here is how to get started.
respR is not yet published in CRAN. For now, use the
devtools package to grab the stable version:
For a quick evaluation of the package, try out the following code:
library(respR) # load the library # As lazy loading is in place, we do not need to call example data explicitly. # This example will use the `urchins.rd` example data. # 1. check data for errors, select cols 1 and 15: urch <- inspect(urchins.rd, 1, 15) # 2. automatically determine linear segment: rate <- auto_rate(urch) # 3. convert units out <- convert_rate(rate, "mg/l", "s", "mg/h/kg", 0.6, 0.4) ## Alternatively, use dplyr pipes: urchins.rd %>% # using the urchins dataset, select(1, 15) %>% # select columns 1 and 15 inspect() %>% # inspect the data, then auto_rate() %>% # automatically determine most linear segment print() %>% # just a quick preview convert_rate("mg/l", "s", "mg/h/kg", 0.6, 0.4) # convert units
Feedback and contributions
respR is under continuous development. If you have any bugs or feedback, you can contact us easily by opening an issue. Alternatively, you can fork this project and create a pull request.
Please also feel free to email with any feedback or problems you may encounter.
- Januar Harianto, University of Sydney
- Nicholas Carey, Scottish Association of Marine Science
- Maria Byrne, University of Sydney
The design of this package would not have been possible without inspiration from the following authors and their packages:
- respirometry - Matthew A. Birk
- rMR - Tyler L. Moulton
- FishResp - Sergey Morozov
- LoLinR - Colin Olito and Diego Barneche
- segmented - Vito M. R. Muggeo
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