| Python re-implementation of predictNLS with Galaxy wrapper
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This Galaxy tool is copyright 2011-2013 by Peter Cock, The James Hutton Institute
(formerly SCRI, Scottish Crop Research Institute), UK. All rights reserved.
See the licence text below.
The tool consists of a Galaxy interface definition (predictnls.xml), and a Python
script (predictnls.py) which re-implements the command line tool predictNLS. This
should match the behaviour of predictNLS v1.0.20 (July 2011), the current latest
release from the Rost Lab, see http://rostlab.org and their paper:
Murat Cokol, Rajesh Nair, and Burkhard Rost.
Finding nuclear localization signals.
EMBO reports 1(5), 411–415, 2000
http://dx.doi.org/10.1093/embo-reports/kvd092
This wrapper is available from the Galaxy Tool Shed at
http://toolshed.g2.bx.psu.edu/view/peterjc/predictnls
Automatic Installation
======================
This Galaxy tool is self contained, and so should install automatically via the
Galaxy Tool Shed.
Manual Installation
===================
There are just four files which should be moved under the Galaxy tools folder,
e.g. in a tools/protein_analysis filter:
* predictlns.xml (the Galaxy tool definition)
* predictlns.py (the Python script)
* predictlns.txt (this README file)
* My_NLS_list (the default set of NLS motifs from the Rost Lab)
You will also need to modify the tools_conf.xml file to tell Galaxy to offer the
tool. If you are using other protein analysis tools like TMHMM or SignalP, put
it next to them. Just add the line::
If you wish to run the unit tests, also move/copy the ``test-data/`` files
under Galaxy's ``test-data/`` folder. Then::
./run_tests.sh -id predictnls
That's it.
History
=======
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Version Changes
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v0.0.4 - Initial public release.
v0.0.5 - Treat non-zero return codes as errors.
v0.0.6 - Link to Tool Shed added to help text and this documentation.
- Use reStructuredText for this README file.
- Updated citation information (Cock et al. 2013).
- Development moved to GitHub, https://github.com/peterjc/pico_galaxy
v0.0.7 - Tool definition now embeds citation information.
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Developers
==========
This script and related tools were initially developed on the following hg branch:
http://bitbucket.org/peterjc/galaxy-central/src/tools
For making the "Galaxy Tool Shed" http://toolshed.g2.bx.psu.edu/ tarball use
the following command from the Galaxy root folder::
$ tar -czf predictnls.tar.gz tools/predictnls/README.rst tools/predictnls/predictnls.xml tools/predictnls/predictnls.py tools/predictnls/My_NLS_list test-data/four_human_proteins.fasta test-data/four_human_proteins.predictnls.tabular
Check this worked::
$ tar -tzf predictnls.tar.gz
tools/predictnls/README.rst
tools/predictnls/predictnls.xml
tools/predictnls/predictnls.py
tools/predictnls/My_NLS_list
test-data/four_human_proteins.fasta
test-data/four_human_proteins.predictnls.tabular
Licence (GPL)
=============
This tool is open source, licensed under the GNU GENERAL PUBLIC LICENSE
version 3 (GNU v3), see http://www.gnu.org/licenses/gpl.html
The Python script is my reimplementation of the original Perl program from
the Rost Lab, which was released under the GPL v3. Therefore, as I consider
this to be a derivative work, this too is released under the GPL v3.
Please note that the My_NLS_list should be an exact copy of the file of the
same name included with predictnls-1.0.7.tar.gz to predictnls-1.0.20.tar.gz
inclusive (the list was extended in v1.0.7 in August 2010, see the change log
included in those tar-balls), available from ftp://rostlab.org/predictnls/
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