Drug response prediction
R package use for predicting drug response of cell lines/patients.
This R package analyzes cancer cell lines /patients gene expression file (Affymetrix U133 plus2.0),
and predicts response to 7 FDA proved cancer drugs (Gemcitabine, Gefitinib, Cisplatin, Doxorubicin,
Docetaxel, Paclitaxel, Carboplatin).
Requirement
This R package requires user to pre-install affy package from bioconductor
Install instruction
R install affy package
source("http://bioconductor.org/biocLite.R")
biocLite("affy")
R install KEADrugResponse package
Download zip file from build folder and use install.package function in R to install
R CMD INSTALL --merge-multiarch KEADrugResponse_*.tar.gz
Unzip file
Usage
library(KEADrugResponse); library(affy);
DrugResponse.predict(patient_inputfile, inputfile_format, sample_name, path_to_model)
Arguments
input_directory directory of gene expression data for patient.
inputfile_format input file format, can be cel (cel file) or exp (gene expression file)
sample_name sample name
path_to_model where the model stored, default to 'KEA_DrugResponse/data'.
return a matrix of positive or negative score for each drug
output pdf files of prediction score for each patient
Example
input .cel file
DrugResponse.predict(input_directory,'cel',patient name,'KEA_DrugResponse/data')
Pipeline
we provide a bash script to run test for cancer samples in pipeline folder.
Each pipeline test uses the model file in KEA_DrugResponse/data (default $DATAPATH) folder.
Change the $DATAPATH variable in pipeline script for different work path
cd into pipeline folder
# cd pipeline
run test for GSE sets
# ./DrugResponse_sample_test_GSE.sh GSE38069
run test for GSM samples
# ./DrugResponse_sample_test_GSM.sh GSM516801
run test for user samples
put all samples in a folder
# ./DrugResponse_sample_test_multi.sh path.to.samples.folder