Work

ceas: an R package for Seahorse data analysis and visualization

Year: 2024

Type: article

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.

Source: Bioinformatics

DOI: 10.1093/bioinformatics/btae503

Authors: Rachel (Rae) J House, James P Eapen, Hui Shen, Carrie R Graveel, Matthew R Steensma

Institutions: Van Andel Institute, Helen DeVos Children's Hospital, Corewell Health, Michigan State University

Language: English

Topic: Data Analysis with R

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $4,188

Funder: National Cancer Institute