CellSim

CellSim calculates cell similarity and predicts co-regulation networks among human cell types to provide molecular-level insights for studies in direct reprogramming, human normal tissues, and cancer.

Key Features:

• Cell Similarity Calculation: Utilizes cell ontology and molecular network data to calculate similarity between over 2,000 human cell types, quantifying positional and functional parallels.
• Regulatory Network Prediction: Identifies shared and co-regulatory networks among subsets of cells to reveal molecular interactions that govern cell behavior and differentiation.
• Gene-Based Cell Type Calculation: Accepts user-provided gene lists to determine matching cell types, supporting over 250 human normal tissue-specific cell types and 130 cancer cell types.
• Data Visualization: Produces results in tabular formats and spider charts for assessment and preservation of similarity and regulatory network data.

Scientific Applications:

• Direct reprogramming target selection: Supports identification of candidate target cells for direct reprogramming by comparing molecular similarity and regulatory networks.
• Cell type annotation in human normal tissues: Enables identification and characterization of tissue-specific cell types from gene lists and similarity metrics.
• Cancer cell type profiling: Facilitates distinction and characterization of cancer cell types using gene-based and network similarity analyses.

Methodology:

CellSim leverages comprehensive datasets encompassing cell ontology and molecular networks and integrates these data sources to compute cell similarities and predict regulatory interactions.