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gcplyr makes it easier to import, wrangle, and do
model-free analyses of microbial growth curve data, as commonly output
by plate readers.
gcplyr can flexibly import all the common data formats
output by plate readers and reshape them into ‘tidy’ formats for
analyses.gcplyr can import experimental designs from files or
generate them in R, and can merge experimental design
information with density data from plate readers.gcplyr makes it easy to analyze growth curve data with
tidyverse or dplyr functions, and to plot
growth curve data with ggplot2.gcplyr can extract parameters like growth rate/doubling
time, maximum density (carrying capacity), lag time, area under the
curve, diauxic shifts, extinction, and more without fitting an equation
for growth to your data.gcplyr has several methods to deal with noise in growth
curve data.Please send all questions, requests, comments, and bugs to mikeblazanin@gmail.com
You can install the version most-recently released on CRAN by running the following line in R:
install.packages("gcplyr")You can install the most recently-released version from GitHub by running the following lines in R:
install.packages("devtools")
devtools::install_github("mikeblazanin/gcplyr")The best way to get started is to check out the online
documentation, which includes examples of all of the most common
gcplyr functions and walks through how to import, reshape,
and analyze growth curve data using gcplyr from start to
finish.
This documentation is also available as a series of pdf vignette files:
Please cite software as:
Blazanin, M. gcplyr: an R package for microbial growth curve data analysis. BMC Bioinformatics 25, 232 (2024). https://doi.org/10.1186/s12859-024-05817-3
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.