Dose-Response Analysis

Version: 1.0.1

Commit Hash: 6648037540ca4e3b63822d9f9d6eea701668995b

Author: CauldronGO Team

Category: analysis

Fit dose-response curves and calculate IC50 values for compound screening data

Install with Cauldron get_app
README

Dose-Response Analysis

Installation

⬇️ Click here to install in Cauldron (requires Cauldron to be running)

Repository: https://github.com/noatgnu/dose-response-analyzer

Manual installation:

  1. Open Cauldron
  2. Go to Plugins → Install from Repository
  3. Paste: https://github.com/noatgnu/dose-response-analyzer
  4. Click Install

ID: dose-response
Version: 1.0.0
Category: analysis
Author: CauldronGO Team

Description

Fit dose-response curves and calculate IC50 values for compound screening data

Runtime

  • Environments: python

  • Entrypoint: dose_response_analyzer.py

Inputs

Name Label Type Required Default Visibility
input_file Input Data File file Yes - Always visible
compound_col Compound Column text No Compound Always visible
concentration_col Concentration Column text No Conc Always visible
response_col Response Column text No Rab10 Always visible
enable_custom_models Enable Custom Models boolean No true Always visible
selection_metric Model Selection Metric select (rmse, aic, bic, r2) No rmse Always visible
show_ic50_lines Show IC50 Lines boolean No true Always visible
show_dmax_lines Show Dmax Lines boolean No true Always visible
file_format Output Format select (svg, png, pdf) No svg Always visible
add_timestamp Add Timestamp boolean No true Always visible
create_overlay Create Overlay Plot boolean No false Always visible
overlay_compounds Overlay Compounds text No - Visible when create_overlay = true
compound_colors Compound Colors text No - Visible when create_overlay = true

Input Details

Input Data File (input_file)

Data file containing compound, concentration, and response values

Compound Column (compound_col)

Column name for compound identifiers

Concentration Column (concentration_col)

Column name for concentration values

Response Column (response_col)

Column name for response values

Enable Custom Models (enable_custom_models)

Include extended set of dose-response models

Model Selection Metric (selection_metric)

Metric used to select the best fitting model

  • Options: rmse, aic, bic, r2

Show IC50 Lines (show_ic50_lines)

Display IC50 reference lines on plots

Show Dmax Lines (show_dmax_lines)

Display Dmax reference lines on plots

Output Format (file_format)

File format for output plots

  • Options: svg, png, pdf

Add Timestamp (add_timestamp)

Add timestamp to output filenames

Create Overlay Plot (create_overlay)

Create a plot with multiple compounds overlaid

Overlay Compounds (overlay_compounds)

Comma-separated list of compounds to overlay on one plot

  • Placeholder: CompoundA,CompoundB,CompoundC

Compound Colors (compound_colors)

Semicolon-separated compound:color pairs for overlay plot

  • Placeholder: CompoundA:#ff0000;CompoundB:#00ff00

Outputs

Name File Type Format Description
summary_table summary_table.txt data tsv Summary statistics for all fitted models
best_models best_models.txt data tsv Best fitting model parameters and IC50 values for each compound
dose_response_plots dose_response*.svg image svg Individual dose-response curve plots for each compound
overlay_plot overlay*.svg image svg Overlay plot with multiple compounds (if overlay_compounds specified)

Requirements

  • Python Version: >=3.11

Python Dependencies (External File)

Dependencies are defined in: requirements.txt

  • click
  • numpy>=1.24.0
  • pandas>=2.0.0
  • matplotlib>=3.7.0
  • dra>=0.1.0

Note: When you create a custom environment for this plugin, these dependencies will be automatically installed.

Example Data

This plugin includes example data for testing:

  input_file: dose_response/example_data.csv
  concentration_col: Conc
  enable_custom_models: true
  show_ic50_lines: true
  create_overlay: false
  compound_col: Compound
  response_col: Rab10
  selection_metric: rmse
  show_dmax_lines: true
  file_format: svg

Load example data by clicking the Load Example button in the UI.

Usage

Via UI

  1. Navigate to analysis → Dose-Response Analysis
  2. Fill in the required inputs
  3. Click Run Analysis

Via Plugin System

const jobId = await pluginService.executePlugin('dose-response', {
  // Add parameters here
});