Cell Layers

Cell Layers visualizes relationships among clusters derived from unsupervised analysis of single-cell transcriptomic data across multiple clustering resolutions using interactive Sankey diagrams to quantify gene expression, co-expression, cluster integrity, and biological process representation.

Key Features:

• Interactive Sankey Visualization: Represents the flow and relationships between cell clusters at different clustering resolutions using Sankey diagrams.
• Multi-resolution Clustering Exploration: Enables dynamic tracking of cluster transitions across multiple clustering resolution parameters.
• Quantitative Gene Expression and Co-expression Analysis: Computes quantitative metrics for gene expression patterns and co-expression networks across resolutions.
• Biological Process Analysis: Links molecular data to biological process representation to evaluate how processes are captured at different resolutions.
• Cluster Integrity Evaluation: Incorporates metrics for assessing cluster stability and integrity across resolutions.

Scientific Applications:

• Cell Population Identification: Facilitates identification and characterization of distinct cell populations within complex tissues by exploring multiple clustering resolutions.
• Insight into Cellular Heterogeneity: Reveals how clusters evolve with resolution changes to provide insight into cellular heterogeneity and underlying biological processes.
• Enhanced Interpretability of Clustering Results: Integrates molecular metrics with cluster evaluation to improve interpretation of single-cell clustering outcomes.

Methodology:

Applies unsupervised clustering algorithms to single-cell transcriptomic data, dynamically visualizes cluster relationships with a Sankey diagram, and computes quantitative metrics for gene expression patterns, co-expression networks, and cluster integrity across resolutions.