Bizard: A Biomedical Visualization Atlas

Bizard is the cover article of iMetaMed Vol 2, Issue 2 (2026). Cover art by Dr. Shixiang Wang.

Welcome 🎉

Data visualization is a critical tool in biomedical research, enabling intuitive interpretation of complex datasets to advance scientific discovery and inform clinical decisions. The R programming language, with its powerful statistical capabilities and extensive package ecosystem, has become a cornerstone for creating high-quality visualizations. However, the vast and ever-evolving landscape of R plotting packages often poses challenges for researchers, who must select appropriate methods and customize visualizations to meet specific research needs. This process demands advanced coding expertise, interdisciplinary collaboration, and significant time investment, which can hinder progress and impact the accuracy of experimental outcomes.

To address these challenges, we developed Bizard, a comprehensive, community-driven platform that integrates a curated repository of visualization codes, advanced tutorials, and collaborative forums. By streamlining access to resources and promoting knowledge exchange, Bizard aims to enhance biomedical researchers’ data analysis capabilities and facilitate the clinical translation of research findings.

What is Bizard?

Bizard brings together powerful visualization tools, curated code, and collaborative features, enabling researchers to streamline data analysis and present their findings in a clear and impactful way.

• Comprehensive Visualization Repository: Bizard consolidates visualization codes from diverse sources, including conventional graphgallery charts and innovative contributions from global experts, providing a state-of-the-art toolkit for biomedical research.

• Versatile Chart Options: The repository features R code implementations for a wide range of visualizations—variable distributions, correlation analyses, ranking plots, and interactive charts—meeting diverse data analysis needs.

• Real-World Applications: Leveraging both native R datasets and authentic biomedical data examples, Bizard enables intuitive understanding and application of visualization techniques in real-world research contexts, accelerating clinical translation.

• Tailored for Biomedical Data: Includes preprocessing algorithms, annotated plotting codes, and specialized methodologies to accommodate the complexities of biomedical datasets, making advanced visualization accessible even to users with limited programming expertise.

• Integrated Statistical Analysis: Combines statistical analysis functions with visualization modules, ensuring rigorous, visually compelling outputs that bolster research reliability and advance evidence-based medicine.

• Collaborative and Open Innovation: Actively invites contributions from biomedical experts to refine features and address evolving data visualization challenges through collective expertise.

• Multi-Platform Accessibility: Offers resources through an open-source GitHub repository with interactive forums and a WeChat official account for tutorials and updates, fostering knowledge sharing and collaboration.

• Driving Research Excellence: Empowers researchers to elevate their data visualization skills, improve methodological standards, and advance precision medicine and personalized therapies.

• Future Vision: Committed to expanding international collaborations and delivering innovative, refined solutions to address the growing complexity of biomedical data visualization and analysis.

Bizard AI Skills

Two ways to give your AI assistant access to Bizard:

• Skill package (static instructions + gallery data): download the Bizard unified skill ZIP and load it into ChatGPT, Claude, Copilot Chat, or a local LLM.
• MCP server (live tool access for AI agents): claude mcp add bizard -- npx @openbiox/bizard-mcp — bilingual search, runnable code, adaptation guidance, citation, and contribution over the Model Context Protocol. Or connect any MCP-capable agent to the public hosted instance with zero install (Claude Code: claude mcp add --transport http bizard http://biotree.top:38123/bizard-mcp/mcp; other clients use the same URL as a Streamable HTTP server; may be faster from mainland China). See the MCP server section in Skills for docs, or mcp/ for source.

Local Development Environment

Contributors who want to render tutorials locally should reproduce the CI environment:

• R packages: the repo pins its R dependency closure in renv.lock (~680 packages, resolved from DESCRIPTION by the Generate renv.lock workflow). Do not edit renv.lock by hand — changes to DESCRIPTION or requirements.txt regenerate it automatically via a PR. To install the locked versions locally:

  install.packages("renv")
  renv::restore(lockfile = "renv.lock", prompt = FALSE)

• Python packages: pip install -r requirements.txt

• Julia tutorials: julia --project=Julia -e 'using Pkg; Pkg.instantiate()'

• Quarto: required to render any page — see https://quarto.org/docs/get-started/.

CI restores the same renv.lock on every build (cache keyed on the lockfile hash), so a successful local restore matches the rendered site.

Citation

If you use Bizard in your research, please cite our paper:

Li, K., Zheng, H., Huang, K., Chai, Y., Peng, Y., Wang, C., ... & Wang, S. (2026). Bizard: A Community‐Driven Platform for Accelerating and Enhancing Biomedical Data Visualization. iMetaMed, e70038. https://doi.org/10.1002/imm3.70038

Public Contributions towards Bizard v2

• https://docs.qq.com/sheet/DSFVkaFVHdFBCSFRw?tab=BB08J2