iSITH

iSITH implements lattice-based spatial simulations of intratumor heterogeneity in R to generate 3D tumor models and synthetic bulk and single-cell DNA sequencing data for studying mutation accumulation and clonal dynamics.

Key Features:

• Efficient Simulation Algorithm: Implements an efficient simulation algorithm that can generate large-scale 3D tumor models containing millions of cells in under a minute.
• Visualization and Summary Plots: Produces visualization and summary plots representing the spatial distribution of mutations within simulated tumors.
• Synthetic Data Generation: Samples from simulated tumor models to produce synthetic bulk and single-cell DNA sequencing datasets.

Scientific Applications:

• Modeling Spatial Drivers of Intratumor Heterogeneity: Investigating how spatial growth processes generate genetic diversity within tumors.
• Studying Mutation Accumulation and Clonal Dynamics: Analyzing mutation accumulation, clonal expansion, and the impact of spatial constraints on evolutionary dynamics.
• Method Development and Benchmarking: Generating synthetic bulk and single-cell DNA sequencing data for development and benchmarking of computational methods.

Methodology:

Simulations use a lattice-based spatial growth model where tumor cells occupy lattice sites and replicate into adjacent sites to produce 3D tumor architectures; efficient algorithms enable rapid, scalable simulation of models with millions of cells.