CheckerboardR a web-tool for synergy calculations

Uploaded Matrix Preview

A preview of the first 100 rows/columns of your uploaded matrix is displayed below. Ensure column names and row names represent concentration levels:

Computed Synergy Summary Statistics

Dose-pair Synergy Barometer

News & Release Notes

August 11, 2026

v2.1.2 Data Provenance & Analysis Extension:
• Added score, reference-effect, observed-response, and ZIP fitted-response matrix views.
• Added matched-replicate SD, SEM, and bootstrap 95% confidence intervals, including labelled 2D heatmaps and full-precision CSV export.
• Added conservative HSA/Bliss/Loewe Consensus analysis, dose-pair synergy barometers, and explicit fitted-baseline correction modes.
• Replaced the duplicated anticancer example and normalized numeric-leading concentration labels across supported sample formats.
• Made bundled sample filenames directly downloadable and derived Drug A/Drug B condition labels from underscore-separated filenames.
• Added an editable Conditions metadata sheet to the Excel example and expanded numerical and Playwright regression coverage.

May 31, 2026

v1.1 Advanced Control & Performance Upgrade:
• Integrated reactive 3D Camera View sliders directly into the sidebar to control azimuth, elevation, and zoom settings for reproducible plotly surfaces.
• Restored the legacy blue-to-yellow color ramp for static 3D plots (`3d_base`) to maintain consistency with published papers.
• Added FAQ section with comprehensive data formatting guide for flawless checkerboard matrix imports.
• Implemented a real-time computation progress bar during reactive synergy evaluations.
• Created a standardized Docker environment for seamless distribution and local execution.

May 30, 2026

v1.0 Complete Engine & Modern Visuals Redesign:
• Full modernization of the R Shiny dashboard with a premium, sleek light theme layout.
• Expanded calculation pipelines to support 4 reference synergy models: HSA, Bliss, Loewe, and ZIP.
• Added 4PL Hill curve-fitting for accurate single-agent concentration-response profiling.

April 23, 2015

v0.1 Legacy Launch:
• Original release with basic cell viability normalization, raw data previews, and early Bliss and HSA calculation routines.

Frequently Asked Questions

Q: What file formats are supported for loading data?

A: The web tool accepts standard tab-separated values (.tab, .tsv), comma-separated values (.csv), as well as structured JSON and XML payloads pasted directly in the input area.

Q: How do the JSON and XML schemas look, and how are they parsed?

A: When pasted, the R backend automatically detects the start tags ({ or <), decodes the payload, and dynamically updates the visual selections (like synergy model, plotting engine, and orientation presets) to generate the graph automatically. Here are the schemas:

Structured JSON Schema Example (Paclitaxel + Carboplatin):

{
  "drug_a": "Paclitaxel",
  "drug_b": "Carboplatin",
  "concentrations_a": [0.0, 0.25, 0.5, 1.0, 2.0, 4.0],
  "concentrations_b": [0.0, 5.0, 10.0, 20.0, 40.0, 80.0],
  "data_type": "viability",
  "matrix": [
    [1.00, 0.95, 0.90, 0.82, 0.70, 0.55],
    [0.92, 0.88, 0.82, 0.73, 0.60, 0.42],
    [0.85, 0.80, 0.72, 0.61, 0.48, 0.32],
    [0.72, 0.65, 0.58, 0.45, 0.35, 0.20],
    [0.55, 0.48, 0.40, 0.30, 0.22, 0.12],
    [0.38, 0.30, 0.22, 0.15, 0.10, 0.05]
  ],
  "settings": {
    "synergy_model": "Bliss",
    "plot_engine": "2d_ggplot",
    "theme_preset": "Nature",
    "orientation": "synergism"
  }
}

Structured XML Schema Example (Fluconazole + Voriconazole):

<drug_combination>
  <drug_a name="Fluconazole">
    <concentrations>0,0.125,0.25,0.5,1.0,2.0</concentrations>
  </drug_a>
  <drug_b name="Voriconazole">
    <concentrations>0,0.015,0.03,0.06,0.12,0.24</concentrations>
  </drug_b>
  <data_representation>viability</data_representation>
  <matrix>
    <row>1.00,0.94,0.88,0.80,0.72,0.65</row>
    <row>0.95,0.89,0.82,0.75,0.68,0.60</row>
    <row>0.88,0.82,0.75,0.68,0.60,0.52</row>
    <row>0.78,0.72,0.65,0.58,0.50,0.42</row>
    <row>0.65,0.58,0.50,0.42,0.35,0.28</row>
    <row>0.50,0.42,0.35,0.28,0.20,0.12</row>
  </matrix>
  <settings>
    <synergy_model>Loewe</synergy_model>
    <plot_engine>2d_ggplot</plot_engine>
    <theme_preset>Science</theme_preset>
    <orientation>synergism</orientation>
  </settings>
</drug_combination>

Q: What is the Model Context Protocol (MCP) server, and how do I configure it?

A: CheckerBoardR.shiny includes an stdio-based Python MCP server (checkerboardr_mcp_server.py). This lets AI assistants (like Claude, Cursor, or Antigravity) programmatically call the synergy calculation engine and save rendered synergy graphs directly to your drive using R. Add the following to your MCP client config file:

{
  "mcpServers": {
    "checkerboardr-mcp": {
      "command": "python3",
      "args": [
        "/home/jw/Source/CheckerBoardR.shiny/checkerboardr_mcp_server.py"
      ]
    }
  }
}

Q: How should the standard delimited matrix rows and columns look?

A: When using raw files, the file must include a header row containing the concentration levels for Drug A (e.g. 0uM, 0.25uM, 0.5uM) and the first column must represent the concentration levels for Drug B. The remaining cells must contain numeric raw cell viability values (such as cell density or OD) or inhibition fractions.

Q: Example format of a standard delimited grid:

conc	0uM	.25uM	.5uM	1uM	2uM
0uM	0.98	0.95	0.90	0.85	0.80
.5uM	0.92	0.88	0.82	0.75	0.70
1uM	0.85	0.80	0.72	0.60	0.55
2uM	0.75	0.70	0.60	0.50	0.42

Q: How do I build and run the Docker container locally?

A: Run these standard shell commands inside the project root directory:

docker build -t checkerboardr .

Then run the container:

docker run -d -p 3838:3838 --name checkerboardr-app checkerboardr

Now, open http://localhost:3838 in your browser to run the full application!