%Remaind: Please install gurobi before running our code (http://www.gurobi.com/)
%Remaind: Please install gurobi before running our code (http://www.gurobi.com/)
%Remaind: Please install gurobi before running our code (http://www.gurobi.com/)
This package includes Matlab scripts and several datasets for demo of network control approach:
(a) main_Benchmark_control.m is a Matlab function for the routine of experimental analysis.
(b) benchmark_control.m is the main script to call Benchmark_control
(c) The input datasets include: % data:the tumor expression data % gene_list:the gene list name data % ref_data:the reference data used in SSN
% index:denotes we use which network construction method
%if index=1,we use CSN
%if index=2,we use SSN
%if index=3,we use SPCC
%if index=4,we use LIONESS
The output datasets include: The sample-specific driver profiles (matrix) by using MMS,MDS,NCU,NCD; For “MMS or MDS,NCU,NCD”, the column is the samples and the rows is the genes. The value “1” denoted that the gene is driver genes;
(d) As a demo, users can directly run main_Benchmark_control.m in Matlab. We choose the single cell time cource data and BRCA cancer data as a test case in our demo. This package has been tested in different computer environments as: Window 7 or above; Matlab 2014 or above.
(e) When users analyzed yourself new data, please: (1) Prepare input datasets as introduced in (d). (2) Clear the previous results. (3) Set parameters in benchmark_control.m as introduced in (b). (4) Run main_Benchmark_control.m. (5) Suggest that the users add all fille in our folders to your folder.
% $Id: main_Benchmark_control.m Created by Weifeng Guo, Zhengzhou University, China at 2020-02-05 21:25:22 $ %
% $If any problem, pleasse contact shaonianweifeng@126.com for help. $