This repository contains the code for the analysis of the drug combination screen on CLL from Lukas, Velten et al. Survey of ex vivo drug combination effects in chronic lymphocytic leukemia reveals synergistic drug effects and genetic dependencies.
The raw data files for this analysis are stored in the EMBL-EBI Biostudies repository (accession number S-BSST381).
The processed data objects can be reproduced by running the preprocessing scripts and are used for the visualization in the Shiny App.
The analysis contains the following parts:
A. Pre-processing
DrugCombi_DataImport.Rmd
: This script takes the raw data files as input and generates data object containing the normalized viability values for each well. Furthermore, it generates a data frame combining the single effect of each drug and the effects of each drug-drug combination.DrugCombi_QC.Rmd
: Some quality control on the data (plate plots, reproducibility between replicates, etc.). Replicates are collapsed to their average values and a filtering threshold is applied on the normalized viability values to remove outliers.DrugCombi_AddOmicsData.Rmd
: Check available omics data for the patients included in the combination screen and show an overview of genetic heterogeneity.
B. Visualization of base drug effects
DrugCombi_BaseAlone.Rmd
: Analyse effect of base compounds alone and their associations to most frequent mutations.
C. Analysis of drug combination effect
DrugCombi_Combi.Rmd
: Analyse effect of drug combinations, associations to most frequent mutations and heatmaps.DrugCombi_CombiSynegy.Rmd
: Investigate synergistic effectsDrugCombi_10x10.Rmd
: Analysis of 10x10 screens
The script plot_utils.R
contains some helper functions for recurrent plots. The script runAll.R
runs the whole analysis starting from the raw data by rendering all the .Rmd files above.
The script Afatinib_targets.Rmd
investigates the expression values of potential tagets of Afatinib.
To reproduce the analysis you need to clone the repository and download the data from the EMBL-EBI Biostudies repository into the data directory. Afterwards, the script runAll.R
can be used to reproduce the full analysis and generate the processed data objects, figures and tables used in the manuscript. The file sessionInfo.txt
gives details about the package versions that were used to reproduce the analysis.