Cellular Energetics Analysis Software
Measuring cellular energetics is essential to understanding a matrix’s (e.g. cell, tissue or biofluid) metabolic state. The Agilent Seahorse machine is a common method to measure real-time cellular energetics, but existing analysis tools are highly manual or lack functionality. The Cellular Energetics Analysis Software (ceas) R package fills this analytical gap by providing modular and automated Seahorse data analysis and visualization using the methods described by Mookerjee et al. (2017).
'ceas' is pronounced like the word 'seas' (siːz, SEEZ).
install.packages("ceas")
You can install the release or development versions from GitHub by cloning the
repo. The code on the main
branch is in sync with the CRAN releases while the
dev
branch has the latest updates. Documentation for the dev branch can be
found on the dev page of the website
(/dev
).
git clone https://github.com/jamespeapen/ceas/
git clone -b dev https://github.com/jamespeapen/ceas/ # dev version
R CMD INSTALL ceas
You can also use the R devtools
package:
devtools::install_github("jamespeapen/ceas")
devtools::install_github("jamespeapen/ceas", ref = "dev") # dev version
or pak
:
pak::pkg_install("jamespeapen/ceas")
pak::pkg_install("jamespeapen/ceas@dev") # dev version
A user guide is available on the package website. Bug reports may be submitted through GitHub issues.
If you use ceas please cite
Rachel (Rae) J House, James P Eapen, Hui Shen, Carrie R Graveel, Matthew R Steensma (2024). ceas: An R package for Seahorse data analysis and visualization, Bioinformatics, 40(8), btae503
Submit patches using GitHub pull requests or by sending a patch file to james.eapen@vai.org. We follow the tidyverse style guide using styler and lintr.
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