ceas: an R package for Seahorse data analysis and visualization

Author:

House Rachel (Rae) J12ORCID,Eapen James P3ORCID,Shen Hui3ORCID,Graveel Carrie R1ORCID,Steensma Matthew R1456ORCID

Affiliation:

1. Department of Cell Biology, Van Andel Research Institute , Grand Rapids, MI 49503, United States

2. Department of Metabolism and Nutritional Programming, Van Andel Research Institute , Grand Rapids, MI 49503, United States

3. Department of Epigenetics, Van Andel Research Institute , Grand Rapids, MI 49503, United States

4. Helen DeVos Children’s Hospital, Corewell Health , Grand Rapids, MI 49503, United States

5. College of Human Medicine, Michigan State University , Grand Rapids, MI 49503, United States

6. Orthopedic Oncology, Corewell Health , Grand Rapids, MI 49503, United States

Abstract

Abstract Summary 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. Availability and implementation ceas is available on CRAN (https://cran.r-project.org/package=ceas). Source code and installable tarballs are freely available for download at https://github.com/jamespeapen/ceas/releases/ under the MIT license. Package documentation may be found at https://jamespeapen.github.io/ceas/. ceas is implemented in R and is supported on macOS, Windows and Linux.

Funder

National Cancer Institute

Publisher

Oxford University Press (OUP)

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