gcplyr
was created to make 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
directly in R
, then merge this design information with
density data.gcplyr
and popular packages
dplyr
and ggplot2
.gcplyr
can calculate plain and per-capita derivatives
of density data.gcplyr
has several methods to deal with noise in
density or derivatives data.gcplyr
can extract parameters like growth rate/doubling
time, carrying capacity, diauxic shifts, extinction, and more without
fitting an equation for growth to your data.Please send all questions, requests, comments, and bugs to mikeblazanin@gmail.com
You can install the most recently-released version from GitHub by running the following lines in R:
install.packages("devtools")
::install_github("mikeblazanin/gcplyr") devtools
You can install the version most-recently released on CRAN by running the following line in R:
install.packages("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,
manipulate, 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, Michael. 2023. gcplyr: an R package for microbial growth curve data analysis. bioRxiv doi: 10.1101/2023.04.30.538883.