GXNA Download Instructions
In addition to the executable (Windows) and the C++ source files
(Linux), the download package contains several required files
(the interaction graphs, the map from gene ID to gene names,
and several probe-to-gene maps) and
some sample data files used to test the program is running correctly.
The software is still under development, so there is some
do-it-yourself involved in its installation and use. However, it
should be fairly straightforward; details below. Once the installation
is complete, read the quick start guide.
WINDOWS
To download, follow these steps:
- save
this
Windows compressed folder to your desktop.
It contains all the files you need.
- right click on the folder and extract to some directory e.g. c:\gxna.
- open a DOS command prompt window and make this the current
directory e.g. cd c:\gxna
- run the following command:
gxna -name sim -mapFile human1av2.ann
The program will run and output some information to the terminal; on
most systems this should take less than one minute.
Once it is finished, type:
more sim_000.res
You should get a list of genes, scores and significance values.
If you use a shell such as Cygwin, you should be able to run GXNA from
within the shell with the exact same command (you may need to use ./gxna
instead of gxna if your path does not include the current directory,
and use less instead of more to display the results).
LINUX/UNIX/MAC
You will need to compile the C++ source files. We have verified that the
code compiles correctly under the Gnu g++ compiler on several Linux systems,
and on Mac OS X (you may need to install g++ on Macs).
To download, follow these steps:
- create a new directory e.g. mkdir gxna
- download
this
compressed TAR archive to the directory.
It contains all the files you need.
- extract the files: tar -xvzf gxna.tar (sometimes Macs decompress
the archive automatically, in which case you should use tar -xvf instead)
- compile the source code: g++ -O3 -o gxna *.cpp
- run the program:
./gxna -name sim -mapFile human1av2.ann
- display the results:
less sim_000.res
You should get a list of genes, scores and significance values.