A Spatial Model of Intratumor Heterogeneity

R package version 1.2.0

Installation

The following is required for installing the package:

• R version 4.0.0 or newer.
• Package Rcpp which can be downloaded from CRAN by running install.packages("Rcpp") from the console.
• Package rgl is strongly recommended for visualizations can be downloaded from CRAN by running install.packages(rgl) from the console.
  • macOS users may have to install Xquartz before installing rgl.

See the package documentation for a complete list of dependencies.

As the package is on CRAN, it can be installed by running install.packages(SITH) from the command line.

Alternatively, the package can be installed directly from this repository by first installing devtools (run install.packages(devtools)) and then running install_github("phillipnicol/SITH") from the console.

Features

• Contains a 3D simulator of spatial tumor growth and mutation, similar to the model described in this paper.
  • The simulator is written in C++ since it is computationally expensive.
  • A tumor with 1 million cells can be simulated in under a minute on a standard desktop computer.
• Simulation of the tumor under targeted therapy.
• 3D interactive visualizations of the simulated tumor using rgl.
  • Option to color regions with high mutation red and regions with low mutation blue.
  • 2D cross section
• Summary of the spatial distribution of mutations throughout the tumor.
  • Creates graphs that show how genetic diversity changes in different spatial regions.
• Create synthetic bulk and single-cell sequencing data from the simulated tumor.
  • Users can specify what part of the tumor the samples are taken from.

Demo

set.seed(1126490984)
library(SITH)
library(rgl)

Generate a tumor with $10^6$ cells:

out <- simulateTumor(max_pop = 1000000, verbose = FALSE)

visualizeTumor(out, background = "white")
rgl::view3d(zoom = 0.66)

visualizeTumor(out, background = "white", plot.type = "heat")
rgl::view3d(zoom = 0.66)

References

If you use SITH in your work, please cite:

Nicol, P.B., Barabasi, D.L., Coombes, K.R. and Asiaee, A. (2022). SITH: an R package for visualizing and analyzing a spatial model of intratumor heterogeneity. Computational and Systems Oncology. Vol 2(2), pg. e1033. https://doi.org/10.1002/cso2.1033.