A bioinformatic classifier of Rab GTPases
Rabifier is an automated bioinformatic pipeline for prediction and classification of Rab GTPases. For more detailed description of the pipeline check the references. If you prefer just to browse Rab GTPases in all sequenced Eukaryotic genomes visit rabdb.org.
Rabifier is freely distributed under the GNU General Public License, check the LICENCE file for details.
Please cite our papers if you use Rabifier in your projects.
- Rabifier2: an improved bioinformatic classifier of Rab GTPases. Surkont J, et al.
- Thousands of Rab GTPases for the Cell Biologist. Diekmann Y, et al. PLoS Comput Biol 7(10): e1002217. doi:10.1371/journal.pcbi.1002217
To install Rabifier simply run
pip install rabifier
Python requirements, third party packages and other dependencies
Rabifier supports Python 2.7 and Python 3.4. Rabifier was tested only on a GNU/Linux operating system, we are not planning to support other platforms.
Rabifier depends on third-party Python libraries:
- biopython (>=1.66)
- numpy (>=1.10.1)
- scipy (>=0.16.1)
Rabifier uses several bioinformatic tools, which are required for most of the classification stages. Ensure that the following programs (or links pointing to them) are available in the system path.
- HMMER (3.1b1): phmmer, hmmbuild, hmmpress, hmmscan
- BLAST+ (2.2.30): blastp
- MEME4 (4.10.2): meme, mast
- Superfamily (>=1.75): superfamily (NOTE: this is a folder containing several Superfamily database files and scripts, see below)
If you have cloned this repository you need to compile the HMMs of Rab subfamilies using hmmpress, i.e. run hmmpress rabifier/data/rab_subfamily.hmm
Rabifier requires a seed database for Rab classification. A precomputed database is a part of this repository. You can also create the database using rabifier-mkdb on the raw, manually curated data sets, available in a seperate repository https://github.com/evocell/rabifier-data. The build process requires additional software.
- CD-HIT (v4.6.4): cd-hit
- PRANK (v.150803): prank
- MAFFT (v7.221): mafft
- matplotlib (>=1.4.3) (optional)
To install Superfamily database follow the instructions below (based on the Superfamily website).
# Register at the Superfamily website to get your username and password # Download files mkdir superfamily cd superfamily wget --http-user USERNAME --http-password PASSWORD -r -np -nd -e robots=off \ -R 'index.html*' 'http://supfam.org/SUPERFAMILY/downloads/license/supfam-local-1.75/' wget http://scop.mrc-lmb.cam.ac.uk/scop/parse/dir.cla.scop.txt_1.75 -O dir.cla.scop.txt wget http://scop.mrc-lmb.cam.ac.uk/scop/parse/dir.des.scop.txt_1.75 -O dir.des.scop.txt # Uncompress files gzip -d *.gz mv hmmlib_1.75 hmmblib # Make Perl scripts executable chmod u+x *.pl # Build the HMM library hmmpress hmmlib # Create a symbolic link pointing to the database directory e.g. ln -s superfamily $HOME/bin/
To run Rab prediction on protein sequences, save sequences in the FASTA format and run:
For more options controlling Rabifier behaviour type:
Bug reports and contributing
Please use the issue tracker to report bugs and suggest improvements.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, Size & Hash SHA256 Hash Help||File Type||Python Version||Upload Date|
(6.7 MB) Copy SHA256 Hash SHA256
|Wheel||py2.py3||Jul 22, 2016|
(6.7 MB) Copy SHA256 Hash SHA256
|Source||None||Jul 22, 2016|