SITH

SITH simulates lattice-based stochastic tumor growth and mutation to model spatial intratumor heterogeneity and produce synthetic sequencing datasets for analysis.

Key Features:

• Lattice-Based Stochastic Modeling: Implements a lattice-based stochastic model that simulates spatial tumor growth and mutational processes.
• 3D Visualizations: Generates three-dimensional visualizations of simulated tumors that represent spatial distributions of mutations and mutation density.
• Synthetic Sequencing Data Generation: Produces synthetic bulk and single-cell sequencing datasets by sampling cells from the simulated tumor environment.
• R Package Implementation: Provided as an R package implementation for computational modeling and data generation.

Scientific Applications:

• Investigating intratumor diversity: Enables study of mechanisms driving intratumor heterogeneity via spatial growth and mutation dynamics.
• Interpreting sequencing data: Supports evaluation of how spatial heterogeneity influences interpretation of bulk and single-cell sequencing results.
• Exploring spatially informed therapies: Facilitates exploration of therapeutic strategies that account for spatial patterns of tumor heterogeneity.

Methodology:

SITH uses a lattice-based stochastic model to simulate spatial tumor growth and mutation, produces 3D visualizations of spatial mutation patterns, and samples simulated tumors to generate synthetic bulk and single-cell sequencing datasets.