HeartMAP: Cardiac Cell-Cell Communication Networks from 287k Single Cells

A dataset of 287,269 cells from seven healthy human heart donors, analyzed to infer cell-cell communication networks across the four cardiac chambers. The data was processed using the HeartMAP computational framework, which integrates single-cell RNA-seq co-expression patterns with ligand-receptor interaction databases. The framework and associated data were last updated in May 2026.

Use Cases

• Identify chamber-specific cell populations based on single-cell RNA-seq expression patterns.
• Model conserved and chamber-specific cell-cell communication networks using inferred ligand-receptor interactions.
• Discover potential therapeutic targets by analyzing differentially expressed genes across chamber pairs.
• Compare inter-chamber signaling similarity, such as between ventricles or atria and ventricles.

Strengths

• Derived from a substantial sample of 287,269 single cells from seven human donors.
• Analysis revealed over 150 significantly different genes per chamber pair, indicating high resolution.
• The framework calculates specific correlation scores (e.g., r = 0.985 between ventricles) and hub scores (0.037–0.047).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect bias inherent to the figshare platform and the specific seven-donor cohort.

Provenance

Source

Single Cell Portal dataset SCP498, processed by Tumo Kgabeng.

Collection Method

Computational analysis of single-cell RNA-seq data integrated with ligand-receptor interaction databases.

Freshness

Last updated 2026-05-12 09:41:40; freshness should be verified.