UMAP
Definition
UMAP (Uniform Manifold Approximation and Projection) is a dimensionality reduction algorithm used to visualize high-dimensional biological data in 2D or 3D space while preserving both local and global data structure. Unlike PCA, UMAP uses manifold learning and topological data analysis to capture non-linear relationships, making it particularly effective for single-cell RNA sequencing, proteomics, and multi-omics datasets. UMAP constructs a high-dimensional graph representation of data, then optimizes a low-dimensional graph to be structurally similar, revealing cell populations, disease subtypes, or molecular clusters that share similar expression profiles or functional characteristics.
Visualize UMAP in Nodes Bio
Researchers can use UMAP-derived clusters as nodes in network visualizations, connecting cell populations or sample groups based on shared molecular signatures, developmental trajectories, or disease states. Network edges can represent transition probabilities between clusters, differential gene expression patterns, or pathway enrichment similarities, enabling exploration of cellular heterogeneity and identification of key regulatory networks driving cluster-specific phenotypes.
Visualization Ideas:
- Cell population networks with UMAP clusters as nodes connected by differentiation trajectories
- Multi-omics integration networks showing relationships between UMAP-derived sample groups
- Drug response networks linking UMAP-identified patient subgroups to therapeutic targets
Example Use Case
A cancer researcher performs single-cell RNA-seq on tumor biopsies from treatment-resistant patients. UMAP analysis reveals six distinct cell populations. By importing UMAP cluster assignments into Nodes Bio, they visualize these populations as nodes connected by shared pathway activities and ligand-receptor interactions. The network reveals that a small resistant subpopulation highly expresses drug efflux transporters and communicates with stromal cells through specific cytokine signaling, suggesting combination therapy targets to overcome resistance mechanisms.