A Python script to simulate 3D tumor growth and multi-region sequencing data via an agent-based model. Deme subdivision is assumed in order to model cell mixing and spatial contraint
- Spatial model: peripheral growth
- Zheng Hu in Curtis lab@Stanford
- Release Date: 2/23/2017
Python packages: numpy,sys,math,random,collections,sets
- Simulation of a typical tumor (~10^9 cells) is computationally costly. We suggest to run this script on HPC cluster.
- The memory cost is also large, e.g. it costs about ~40G when the final_tumor_size = 10^9 and mut_rate = 0.6.
To run the script
$ python 3DTumorSimul_MultiRegionSeq.py deme_size mut_rate adv_rate s_coef repl
e.g., python 3DTumorSimul_MultiRegionSeq.py 5000 0.6 0.00001 0.1 0