A Transparent Analysis Pipeline for Mammalian Metabolic Phenotype Microarray Data R package MetPhenoR version 1.3 Provides a transparent, end-to-end workflow for analyzing high-throughput phenotype microarray data in mammalian cell cultures. It begins with automated reading and noise correction, followed by comprehensive quality control via visual diagnostics, i.e. detecting missing wells, anomalous curve shapes and variance. Area under Curve is computed as a summary metric. Biological annotations (custom or in-built for PM-M01,PM-M02, PM-M11 - PM-M14) enable group-level comparisons. Software Depends: R (>= 4.5.0) Imports: readr, dplyr, magrittr, tidyselect, ggplot2, tidyr, stringr, purrr, tidyselect, scales, stats, patchwork, readr, ggforce, rlang Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Katja Danielzik <katja.danielzik@uni-due.de> Comprehensive R Archive Network (CRAN) Katja Danielzik [aut, cre, cph] (ORCID: <https://orcid.org/0009-0007-5021-6212>), Willson Tjioe [aut] (ORCID: <https://orcid.org/0009-0003-3530-1727>), Julia Asche [ctb], Johann Matschke [ctb] (ORCID: <https://orcid.org/0000-0003-4878-8741>), Daniel Hoffmann [ctb] (ORCID: <https://orcid.org/0000-0003-2973-7869>) GPL (>= 3) 2026-11-11 application/tgz https://CRAN.R-project.org/package=MetPhenoR doi:10.32614/CRAN.package.MetPhenoR