pyLinG3D 0.3

Visualizing the Spatio-Temporal Dynamics of Clonal Evolution

pyLinG3D: Visualizing the Spatio-Temporal Dynamics of Clonal Evolution

This library is a python implementation of the LinG3D (https://github.com/rejniaklab/LinG3D) which generates the 3D lineage trees of (1) all clones; (2) individual clones; (3) all clones, but with only those cells that survived to the end of simulation; and (4) individual clones containing only those cells that survived to the end of simulation.

Installing with pip

if you are using Linux or macOS you can install pyLinG3D with pip

pip install pyLinG3D

Example

%matplotlib ipympl

from pyLinG3D import LinG3DClone
from platform import python_version
print(python_version())

#exampleB05

pathData='exampleB05'
cloneNum=5
toPrint=1                # save the final figure
IsGradient = 1           # draw drug gradient in the background 1-yes; 0-no;
xmin=-100; xmax=100; ymin=xmin; ymax=xmax  # 2D domain boundaries
tmin=0; tmax=100000                        # time/iteration boundaries
fileStep = 2000       # frequency of data 
    
LinG3DClone(pathData,cloneNum,IsGradient,xmin,xmax,ymin,ymax,tmin,tmax,fileStep,toPrint).linG3DClone()

Authors

Anjun Hu, Maureiq Ojwang’, Kayode Olumoyin [e-mail], Katarzyna Rejniak

Acknowledgements

This work was supported by the NIH/NCI grants CA259387 and CA272601, and the NIH/NCI Physical Sciences Oncology Network (PSON) grant CA202229.