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PathNet Installation Instructions
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June 27, 2012


PathNet is a set of R routines for pathway analysis using topological 
information. You will need to have a working installation of R before using 
PathNet.  R can be obtained from http://cran.r-project.org/, this version of 
PathNet has been tested with R 2.14.1.


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Installation
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You should have received a zip archive file containing PathNet along with this 
installation guide. In order to use the PathNet functions and datasets you will 
first need to extract the contents of the PathNet.zip file.  You can use an 
unzip tool that may have been included with your operating system, or use 
third-party software such as Unzip, WinZip or 7-zip.

Windows Example
1) Using Windows, navigate to the directory where you saved the 
PathNet.zip file.

2) Use your unzip tool to extract the contents of the PathNet.zip file.  In 
general, you can use unzip tools by right-clicking the zip file, selecting the 
tool name, then selecting an extract operation.

3) Make note of the directory where the contents were extracted and stored as
you will need to use this location as your R working directory.


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Contents
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After extracting the contents of the PathNet.zip archive file you should have
a folder containing the functions and datasets required to run PathNet in an
R environment.  

This directory should include the following files:

* adjacency_data.txt
  Dataset containing the adjacency matrix of the connectivity information among 
  genes in the pooled pathway.

* brain_regions_data.txt
  Dataset of the comparison of gene expressions from each of the six brain 
  regions with corresponsing control samples.

* disease_progression_data.txt
  Dataset of the comparison of the gene expression from incipient, moderate,
  and sever samples with control samples.

* PathNet.RData
  Main R file containing functions implementing the PathNet algorithms.

* pathway_data.txt
  Dataset consisting of pooled pathways combined from the KEGG database.

* PathNet_Manual.docx 
  Manual for PathNet containing detailed usage information.


PathNet ships with datasets developed and used in a study involving measured 
microarray gene expressions of Alzheimer's disease patients.  The dataset files
included are simple text files that are tab separated with row or column names 
contained in double quotes.  These text files are provided as an example of 
the input formats used for PathNet so users can construct their own datasets 
for analysis.  Versions of these datasets in a native R format are also 
contained and accessible from the PathNet.RData data file.


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PathNet and the R Working Directory
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You will need to ensure you have the PathNet.RData file available in your R
session working directory in order to make use of the PathNet functions and 
datasets.  The R working directory is the main directory for a session where 
user scripts and datasets are stored.  You can either set your working directory
to be the location where you extracted the PathNetfiles, or copy the extracted
PathNet files to a different directory you wish to use.

If you use the console version of R, navigate to the directory containing these 
files before starting your R environment.  If you use a graphical version of R 
or started a console session of R in a different directory, you will need to 
explicitly set your working directory to be the same as the location of these 
files from the R interpreter.

In order to set the current working directory within R, use the "setwd" command.
For example,

> setwd('d:/PathNet')

where 'd:/PathNet' is the location of the directory you wish to use.  You should
use forward slashes when telling R which directory to use, even when using 
Microsoft Windows operating systems.

You can verify you have set the working directory to the correct location for
PathNet by using the "dir" command and checking that the "PathNet.RData" file
is available.  For example,

> dir()
[1] "adjacency_data.txt"          
[2] "brain_regions_data.txt"      
[3] "disease_progression_data.txt"
[4] "PathNet.RData"               
[5] "PathNet_Manual_01_31.docx"   
[6] "pathway_data.txt"

Once the working directory has been set, you must load the R workspace image 
containing the PathNet functions and datasets.  You can use the "load" command 
to load the dataset, and the "ls()" command to verify that the functions and 
datasets have been successfully loaded into your R environment.

> load('PathNet.RData')
> ls()
[1] "A"                   "brain_regions"       "disease_progression" "PathNet"
    "pathway"


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Next Steps
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Review the PathNet Manual for more detailed information and examples of using
the PathNet datasets and functions.