Code to accompany the paper: "Computational quantification and characterization of independently evolving cellular subpopulations within tumors is critical to inhibit anti-cancer therapy resistance"

Link to the paper: https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-022-01121-y

1. Introduction

All equations and detailed information are elaborated in the "Methods" section of the paper. The code can be implemented in any programming language (e.g., Python, R). Here we provide MATLAB scripts for computing G and λ values.

2. Scripts

1. script1_lambdaandGcalculatons.m - Translates the equations from the paper to MATLAB code.
2. script2_alternative_lambdaandGcalculatons.m - Uses MATLAB's SVD (Singular value decomposition) algorithm in order to compute G and λ values.

Input

In both scripts the variable data is the input matrix, where each column represents a particular protein, and each row is a cell i. Examples of data inputs are presented as in supplementary tables S2-S7.

Output

The generated variables (matrices lambda and G) represent λ_α(cell) and G_iα values as explained in the Methods.