https://github.com/luispedro/coelho2013_bioinformatics
Reproducible code archive for http://dx.doi.org/10.1093/bioinformatics/btt392
https://github.com/luispedro/coelho2013_bioinformatics
Last synced: 2 months ago
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Reproducible code archive for http://dx.doi.org/10.1093/bioinformatics/btt392
- Host: GitHub
- URL: https://github.com/luispedro/coelho2013_bioinformatics
- Owner: luispedro
- Created: 2013-07-19T16:04:07.000Z (almost 13 years ago)
- Default Branch: master
- Last Pushed: 2015-10-07T08:29:11.000Z (over 10 years ago)
- Last Synced: 2025-01-19T06:43:44.370Z (over 1 year ago)
- Language: Python
- Homepage:
- Size: 120 KB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.rst
- Citation: CITATION.rst
Awesome Lists containing this project
README
Source code for paper *Determining the subcellular location of new proteins
from microscope images using local features* by Coelho et al. in
`Bioinformatics `__
This repository is **for reproduction of the results in the paper**. If you
want to apply the methods to your data, check out the `tutorial on doing so
`__.
It is a step by step manual on applying the methods to your data.
Dependencies
------------
::
sudo apt-get install python python-pip python-virtualenv
sudo apt-get install dvipng
Instructions
------------
1. For the Human Protein Atas data, please download from
http://murphylab.web.cmu.edu/software/2012_PLoS_ONE_Reannotation/
Edit the file ``sources/hpa.py`` to point to where you downloaded all the data.
2. Get the randtag data from
http://murphylab.web.cmu.edu/software/2013_Bioinformatics_LocalFeatures/ or
from `Data Dryad `__
3. The remaining data should be automatically downloaded when you run::
doitall.sh
This will also run the computation.
If you want to take advantage of multiple processors, edit the file
``doitall.sh`` and set the ``NR_CPUS`` variable. Note that the whole
computation (i) takes a very long time (days) on a single core and (ii) is
designed to take full advantage of multiples cores.
Citation
--------
For referring to this work, please cite:
*Determining the subcellular location of new proteins from microscope images
using local features* by Luis Pedro Coelho, Joshua D. Kangas, Armaghan Naik,
Elvira Osuna-Highley, Estelle Glory-Afshar, Margaret Fuhrman, Ramanuja
Simha, Peter B. Berget, Jonathan W. Jarvik, and Robert F. Murphy (2013).
Bioinformatics, [`DOI `__]