Cancer biomarker discovery is improved by accounting for variability in general levels of drug sensitivity in pre-clinical models

This repository contains the code and data to reproduce the results from the paper "Cancer biomarker discovery is improved by accounting for variability in general levels of drug sensitivity in pre-clinical models". The attached zip file contains a file called "index.html" that contains links and instructions to all of the scripts used to produce the results and figures in the paper. 

Paper Abstract:

We show that variability in general levels of drug sensitivity in pre-clinical cancer models confounds biomarker discovery. However, using a very large panel of cell lines, each treated with many drugs, we could estimate a “general level of sensitivity to all drugs” in each cell line. By conditioning on this variable, biomarkers were identified that were more likely to be effective in clinical trials than those identified using a conventional uncorrected approach. We find that differences in general levels of drug sensitivity are driven by biologically relevant processes. We developed a gene expression based method that can be used to correct for this confounder in future studies.