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ClusterChirp

An interactive heatmap visualization tool for exploring tabular data with on-the-fly clustering, correlation networks, pathway analysis, and an AI-powered chatbot. Built for researchers and data scientists.

Live demo: https://clusterchirp.mssm.edu

Quick Start with Docker

The easiest way to run ClusterChirp locally is with Docker. No setup required.

docker pull ghcr.io/gumuslab/clusterchirp:latest
docker run -p 8080:80 ghcr.io/gumuslab/clusterchirp:latest

Then open http://localhost:8080 in your browser.

Enable AI Chat (Optional)

The built-in AI chatbot lets you interact with your heatmap using natural language commands (e.g., "show top 20 most variant genes", "cluster rows", "sort by variance"). It requires an OpenAI API key.

docker run -p 8080:80 -e OPENAI_API_KEY=sk-your-key ghcr.io/gumuslab/clusterchirp:latest

You can get an API key at https://platform.openai.com/api-keys.

All other features (heatmap visualization, clustering, correlation networks, pathway analysis) work without an API key.

Features

  • Interactive Heatmap — Upload CSV, TSV, or XLSX files and visualize with real-time clustering
  • AI Chatbot — Natural language commands to filter, sort, cluster, and explore your data
  • Correlation Networks — Visualize gene correlation networks in 2D and 3D
  • Pathway Analysis — Enrichment analysis with KEGG, Reactome, WikiPathway, and more
  • Example Datasets — Preloaded proteomics, genomics, and immunogenomics datasets to explore

Development Setup

Prerequisites

Frontend

npm install
npm start

Runs on http://localhost:3000.

Backend

See the HeatmapBackend repo for backend setup instructions.

Architecture

Component Technology
Frontend React, TypeScript, deck.gl, MUI
Backend Django, Django REST Framework
Clustering scipy, scikit-learn, numba
AI Chat OpenAI GPT-4o-mini
Docker nginx + gunicorn + supervisord

Citation

If you use ClusterChirp in your research, please cite:

Rawal, O., et al. "ClusterChirp: A GPU-accelerated Web Server for Natural Language-Guided Interactive Visualization and Analysis of Large Omics Data." arXiv preprint (2026). https://doi.org/10.48550/arXiv.2602.08280

License

This project is developed by the Gumus Lab at the Icahn School of Medicine at Mount Sinai.

ClusterChirp is freely available for all users. No registration required.

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