gcplyr: Wrangle and Analyze Growth Curve Data

Easy importing, wrangling, and model-free analysis of microbial growth curve data, as commonly output by plate readers. Tools for flexibly importing all the common data formats output by plate readers and reshaping them into 'tidy' formats for analyses. Tools for importing experimental designs from files or generating them in R and merging design information with density data, making it easy to analyze with 'gcplyr' and 'tidyverse' or 'dplyr' functions, and to plot with 'ggplot2'. Streamlines extracting 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. Has several methods to deal with noise in growth curve data. See methods at <https://mikeblazanin.github.io/gcplyr/>.

Version: 1.13.1
Depends: R (≥ 2.10)
Imports: dplyr, rlang, stats, tidyr, tools, utils
Suggests: caret, cellranger, ggplot2, knitr, lubridate, mgcv, readxl, rmarkdown, sf, testthat (≥ 3.0.0), xlsx
Published: 2026-10-17
DOI: 10.32614/CRAN.package.gcplyr
Author: Mike Blazanin ORCID iD [aut, cre]
Maintainer: Mike Blazanin <mikeblazanin at gmail.com>
License: MIT + file LICENSE
URL: https://mikeblazanin.github.io/gcplyr/, https://github.com/mikeblazanin/gcplyr/
NeedsCompilation: no
Citation: gcplyr citation info
Materials: README, NEWS
CRAN checks: gcplyr results

Documentation:

Reference manual: gcplyr.html , gcplyr.pdf
Vignettes: Introduction to using gcplyr (source, R code)
Importing and reshaping data (source, R code)
Incorporating experimental designs (source, R code)
Pre-processing and plotting data (source, R code)
Processing data (source, R code)
Analyzing data (source, R code)
Dealing with noise (source, R code)
Best practices and other tips (source, R code)
Working with multiple plates (source, R code)
Using make_design to generate experimental designs (source, R code)

Downloads:

Package source: gcplyr_1.13.1.tar.gz
Windows binaries: r-devel: gcplyr_1.12.0.zip, r-release: gcplyr_1.12.0.zip, r-oldrel: gcplyr_1.12.0.zip
macOS binaries: r-release (arm64): gcplyr_1.12.0.tgz, r-oldrel (arm64): gcplyr_1.12.0.tgz, r-release (x86_64): gcplyr_1.12.0.tgz, r-oldrel (x86_64): gcplyr_1.12.0.tgz
Old sources: gcplyr archive

Linking:

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