Analyze disease genes vs. transcriptome data, for in silico screening for drug repositioning (R code)
R
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
R
data
LICENSE
README.md

README.md

drugscan: Software for in silico drug repositioning, based on analysis of Connectivity Map 2.0 data and disease gene sets. This software accompanies the manuscript "A computational systems biology approach for identifying candidate drugs for repositioning for cardiovascular disease", by Alvin Yu and Stephen Ramsey, which has been submitted to the journal Interdisciplinary Life Sciences: Computational Life Science".

Author: Alvin Yu, Oregon State University

From the lab of: Stephen Ramsey, Oregon State University (lab.saramsey.org)

Date: February 17, 2016

This software is distributed under the Apache Software License 2.0. Please see the file LICENSE for details on the software licensing agreement.

Usage notes: There are three R scripts in the subdirectory "R", that comprise this software release. The scripts load tab-delimited text datafiles, examples of which are given in the subdirectory "data". Each of the example datafiles contains the first ten lines of the actual datafile used in the analysis. All of the example datafiles have Unix line termination. The three R scripts are used in this order:

(1) statistical_test.R (2) ks_drugbank_test.R

The script "synthetic_data_analysis.R" creates the synthetic dataset used for the analysis of optimal weight values for the gene set scoring (see Table 1 in the above-referenced manuscript).