CancerSimulator is a tool to simulate cancer evolution as a selective model driven by mutations and Copy Number (CN) changes. It is designed to reproduce data from single-cell DNA sequencing such as Direct Library Preperation + (DLP+).

Installation

You can install CancerSimulator with the following command

devtools::install_github("dinhngockhanh/CancerSimulator")

Input data

CancerSimulator takes as input several csv files that dictate the evolution model. The user can either create them from scratch or by using a suite of R functions. The prefix * in the filenames must match the model name to be given later to the simulator.

Model variables

The file *-input-variables.csv contains the model variables, including the beginning and final time for the simulations, cell lifespan, size of CN bin, rate of driver mutations and probabilities of CN events.

Sampling information

The file *-input-sampling.csv contains the time where each sample is taken, cell count in each sample, and a name for the sample.

Chromosome bin count and centromere location

The file *-input-copy-number-blocks.csv contains the length of each chromosome as number of bins, as well as the location of its centromere also as bin index.

Population dynamics

CancerSimulator is designed so that the total cell population follows a given dynamics. This is given in the file *-input-population-dynamics.csv, which lists the time points and desired population sizes at those time points. Within two time points, the simulator interpolates to find the desired population size.

Driver gene library.

The file *-input-cancer-genes.csv contains information of driver genes to be included in the model. Each gene should be given a role (TSG/ONCOGENE) and the location on the genome (chromosome & bin). The selective strength s for the gene is encoded in Selective_strength; larger s means the mutated driver is more likely to be fixated and its fixation takes less time. There are two selection rates for each gene, s_rate_WT for the WT allele and s_rate_MUT for the mutated allele. These rates are computed from Selective_strength according to the following formula:

• For TSG's, s_rate_WT=1/(1+s) and s_rate_MUT=1
• For oncogenes, s_rate_WT=alpha and s_rate_MUT=alpha*(1+s) where alpha is such that the product of all s_rate_WT is 1.

Initial population

The information about the initial cell population is given in two files. The file *-input-initial-others.csv lists the clones in the population, their cell counts, and mutated drivers. The file *-input-initial-cn-profiles.csv specifies the CN profile of each clone. For each clone and for each chromosome, we need to specify the allele identity of each strand.

Run the simulator

There are several stages for how far the simulator will do, depending on what the user requires from the simulations. The variable stage_final dictates this:

• stage_final=1 only produces the clonal evolution.
• stage_final=2 samples cells as specified above, and outputs their CN profiles as a rda file.
• stage_final=3 further builds the phylogeny for these cells, and outputs this as a rda file. The phylogeny is built based on information from the clonal evolution.

N_clones_min and N_clones_max are optional variables in case we want to limit the number of clones in the simulation.

To produce one simulation for model *, we can call

simulation <- SIMULATOR_FULL_PROGRAM_one_simulation(model=*,stage_final=stage_final,N_clones_min=N_clones_min,N_clones_max=N_clones_max)

See the vignettes for further analyses that can be performed from simulation.