Step 1: Construct a list of KEGG pathway names and include it into a text file called pathways.txt
Step 2: Run the R Script getKEGGPathways.R to create a directory of pathways in a format suitable to be loaded by the java program

Step 3: Run the runPriors.jar file using Java
 Example: java -jar runPriors.jar <arguments>
 
 The arguments you can specify are as follows:
 
 
 
 
Required Arguments:
 
 
-run <Run Name>
Name of the current job, all results will be placed in a folder with this names

-priors <Prior Directory>
Just specify the path to the directory created by the R Script

-data <dataFile>
The filename of the expression dataset, genes should be in columns, and samples in rows





Optional Arguments:
 
-ns <Number of Subsamples> 
Number of subsamples to use to compute edge stabilities
Usually you will set this around 10-20 depending upon the number of samples you have
Default:20

-nl <Number of Lambda Values>
Number of sparsity parameter values to test
A larger number will increase accuracy, but will greatly increase runtime
Default:40


-sif
Specify this switch if the prior information is in the form of an .sif file instead of a matrix
Example: ADCY9	TP53
		CHEK1	IFNG


-loocv 
Use this switch if you have less than 50 or so samples to do Leave-one-out cross validation instead