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Welcome to HeartMAP

HeartMAP (Heart Multi-chamber Analysis Platform) is a specialized bioinformatics package that decodes cellular communication across all four chambers of the human heart. Unlike general single-cell tools, HeartMAP is purpose-built for cardiac biology, offering chamber-specific insights crucial for understanding heart function, disease, and therapeutic opportunities.
Published in Computational and Structural Biotechnology Journal (2025)Read the paper | DOI: 10.1016/j.csbj.2025.11.015

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Why HeartMAP?

Understanding cell-cell communication within and between the four distinct cardiac chambers is fundamental to elucidating cardiac function and disease mechanisms. Each chamber exhibits unique cellular and molecular characteristics that reflect specialized physiological roles, yet existing frameworks for mapping chamber-specific intercellular networks have remained limited. HeartMAP addresses this gap by providing a computational framework that infers cardiac cell-cell communication networks at chamber resolution through integration of single-cell RNA-seq co-expression patterns and ligand-receptor interaction databases.

Production Ready

Fully tested, documented, and deployed on PyPI with comprehensive validation on real human heart datasets

Multiple Interfaces

Access HeartMAP through CLI, Python API, REST API, or Web interface - whatever fits your workflow

Easy Installation

Install with a single command: pip install heartmap and start analyzing in minutes

Memory Optimized

Configurable memory usage works on systems with 8GB+ RAM with intelligent subsetting

Chamber-Specific

Analyze all four cardiac chambers (RA, RV, LA, LV) with specialized markers and communication patterns

Comprehensive

From basic QC and cell typing to advanced communication analysis and multi-chamber insights

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Key Features

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Analysis Pipelines

HeartMAP provides multiple analysis pipelines to suit your needs:
PipelinePurposeOutputRuntime
BasicQuality control, cell typingCell annotations, QC metrics5-10 min
CommunicationCell-cell interactionsCommunication networks, hubs10-15 min
Multi-ChamberChamber-specific analysisChamber markers, comparisons15-20 min
ComprehensiveComplete analysisAll of the above + reports20-30 min

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Scientific Results

Using a dataset of 287,269 cells from seven healthy human heart donors, HeartMAP has identified:
  • Chamber-specific cell populations with unique markers for RA, RV, LA, and LV
  • Communication networks revealing both conserved and chamber-specific signaling pathways
  • Communication hubs with atrial cardiomyocytes and adipocytes as key signaling centers (hub scores: 0.037-0.047)
  • Cross-chamber correlations showing highest similarity between ventricles (r=0.985) and lowest between LA and LV (r=0.870)
HeartMAP has identified over 150 significantly different genes per chamber pair, establishing a molecular foundation for precision cardiology approaches.

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Use Cases

Pharmaceutical Research

Drug target discovery and safety assessment with chamber-specific therapeutic targets

Clinical Cardiology

Precision medicine and disease mechanism understanding for better patient outcomes

Basic Research

Cardiac development studies, evolutionary biology, and fundamental cardiac research

Computational Biology

Method benchmarking, data integration, and pipeline development

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Performance

HeartMAP is optimized for various hardware configurations:
HardwareDataset SizeMemoryRuntimeStatus
8GB RAM30K cells~6GB15 min✅ Recommended
16GB RAM50K cells~12GB25 min⚡ Optimal
32GB RAM100K cells~24GB45 min🚀 Production

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Getting Started

Ready to start analyzing cardiac single-cell data? Here’s what to do next:

Install HeartMAP

Install HeartMAP and verify your setup

Quick Start Guide

Run your first analysis in minutes

API Reference

Explore the Python API in depth

Tutorials

Learn advanced features and workflows

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Scientific Impact

HeartMAP enables:
  • Clinical Applications: Chamber-specific therapeutic strategies for improved treatment outcomes
  • Research Advances: First comprehensive multi-chamber communication atlas
  • Education: Accessible cardiac biology analysis platform for students and researchers
  • Industry Tools: Production-ready bioinformatics tool for pharmaceutical and biotech companies

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Citation

If you use HeartMAP in your research, please cite our paper: 
@article{KGABENG2025,
  title = {HeartMAP: A Multi-Chamber Spatial Framework for Cardiac Cell-Cell Communication},
  journal = {Computational and Structural Biotechnology Journal},
  year = {2025},
  issn = {2001-0370},
  doi = {https://doi.org/10.1016/j.csbj.2025.11.015},
  author = {Tumo Kgabeng and Lulu Wang and Harry Ngwangwa and Thanyani Pandelani},
  keywords = {single-cell RNA-seq, cell-cell communication, cardiac chambers, 
              spatial transcriptomics, therapeutic targets}
}
Next Steps: Install HeartMAP to get started, or jump directly to the Quick Start Guide to see it in action.

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