CellScape

CellScape visualizes single-cell genomic data and phylogenetic relationships to analyze clonal evolution in heterogeneous cell populations.


Key Features:

  • Single-Cell Phylogeny Visualization: Displays evolutionary relationships among individual cells using phylogenetic trees provided as edge lists.
  • Genomic Heatmap Integration: Links phylogenetic structures with heatmaps representing locus-specific mutation calls or copy-number states for each cell.
  • Flexible Phylogeny Representation: Supports multiple phylogenetic formats including dendrograms and evolutionary trees with observed or latent internal nodes.
  • Copy Number and Mutation Data Support: Processes per-cell genomic profiles derived from copy-number segmentation or targeted mutation calls.

Scientific Applications:

  • Single-Cell Cancer Evolution Analysis: Investigates clonal evolution, mutation accumulation, and lineage diversification in tumor cell populations.
  • Genomic Heterogeneity Studies: Examines variation in mutation and copy-number states across individual cells.
  • Phylogenetic Interpretation of Single-Cell Data: Integrates genomic profiles with evolutionary trees to study tumor progression, treatment resistance, and metastatic dissemination.

Methodology:

CellScape integrates per-cell genomic profiles such as copy-number segment data or targeted mutation calls with a single-cell phylogeny provided as an edge list, and generates synchronized visualizations combining phylogenetic trees with genomic heatmaps representing mutation or copy-number states across cells.

Topics

Collections

Details

License:
GPL-3.0
Maturity:
Mature
Cost:
Free of charge
Tool Type:
plugin
Operating Systems:
Linux, Windows, Mac
Programming Languages:
R
Added:
6/5/2018
Last Updated:
11/25/2024

Operations

Data Inputs & Outputs

Genetic variation analysis

Publications

Smith MA, Nielsen CB, Chan FC, McPherson A, Roth A, Farahani H, Machev D, Steif A, Shah SP. E-scape: interactive visualization of single-cell phylogenetics and cancer evolution. Nature Methods. 2017;14(6):549-550. doi:10.1038/nmeth.4303. PMID:28557980.

Documentation

Downloads