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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
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