multiplot: Approximating statistical plot styles across nine graphing software packages and an academic publication style in R

Background Biomedical researchers routinely switch between graphing tools such as GraphPad Prism, SPSS, OriginPro, Stata, and MATLAB, each with distinctive default visual conventions. This heterogeneity can make otherwise correct R figures appear unfamiliar to collaborators or reviewers accustomed to another software environment. Methods We developed multiplot, an open-source ggplot2 extension that provides software-derived style approximation layers for nine graphing packages and one academic publication style. ggchoice() applies a complete theme, discrete colour scale, and discrete fill scale in one call, while include_scales = FALSE allows theme-only use. We formalised styles using a five-component Plot Style Ontology and extracted parameters from documentation, scheme files, and direct output inspection. Default palettes were assessed for colour vision deficiency (CVD) safety, grayscale print fidelity, and approximate print-colour risk. Results multiplot exports 29 user-facing functions, is implemented entirely in R, and requires only ggplot2 for core plotting. Prism, SPSS, and MATLAB styles were verified against real software screenshots; other software-derived styles were checked against documentation, user guides, scheme files, or selected screenshots where available. The Academic style is an internally defined publication-oriented benchmark. In the compliance assessment, Academic and SigmaPlot achieved the maximum scores; the most common vulnerability was reduced colour separability under simulated CVD, including red-green confusion in several colour-based palettes. Conclusions multiplot provides a multi-software ggplot2 style approximation tool with a formal ontology framework, reproducible examples, and publication compliance guidance.