pcvr provides R functions for use with PlantCV output or other phenotype data with the goal of lowering the barrier to entry for Bayesian statistics and non-linear modeling.
Installation
The release version of pcvr can be installed from CRAN
install.packages("pcvr")
library(pcvr)Alternatively the development version of pcvr can be installed using remotes/devtools install_github as shown below. Note that the default behavior in devtools/remotes is to only install true dependencies. Some functions in pcvr use specific packages that would otherwise not be needed for most work, notably the brms modeling functions. To install suggested packages (see DESCRIPTION file) add dependencies=T to the install_github function call.
Vignettes
See the Vignettes tab above for several example workflows for common plant phenotyping tasks.
Tutorials
See the Quarto Tutorials tab above for links to Quarto presentations on github that go more in depth about the rationale behind several pcvr functions/options.
Function Reference
Functions are separated by broad goal/type of data they use under the Functions tab above.
Getting started
Please see the bellwether vignette (named for the high throughput phenotyping facility at the Donald Danforth Plant Science Center) for a general introduction to pcvr.
vignette("bellwether", package="pcvr")
# or
browseVignettes("pcvr")Feedback
Please report bugs and make feature requests with issues the github page.