We introduce bregr, a novel open-source R package designed to streamline batch processing and visualization of biomedical regression models. Addressing the inefficiency and reproducibility challenges of manually constructing multiple univariate and multivariate models, bregr provides a cohesive, tidyverse-style workflow. Built on the S7 object-oriented framework for extensibility, it supports diverse models—including generalized linear, Cox proportional hazards, and mixed-effects models—leveraging native R pipes, parallel computing, and robust error handling. Key features include automated model fitting for variable combinations, tidy result extraction, integrated publication-quality visualizations (e.g., forest plots), and a one-step pipeline function. Validated on TCGA cohorts, bregr enhances efficiency, scalability, and reproducibility for large-scale biomedical data analysis. The package is available on CRAN and GitHub.
Med Research
Data/statistical analysis
Human tissue samples
bregr: An R Package for Streamlined Batch Processing and Visualization of Biomedical Regression Models
17-Sep-2025
The authors declare no conflicts of interest.