Skip to main content
Warning: You are using the test version of PyPI. This is a pre-production deployment of Warehouse. Changes made here affect the production instance of TestPyPI (
Help us improve Python packaging - Donate today!

A bioinformatic classifier of Rab GTPases

Project Description

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

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 The build process requires additional software.

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*' ''
wget -O dir.cla.scop.txt
wget -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:

rabifier sequences.fa

For more options controlling Rabifier behaviour type:

rabifier -h

Bug reports and contributing

Please use the issue tracker to report bugs and suggest improvements.

Release History

Release History

This version
History Node


History Node


History Node


Download Files

Download Files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
rabifier-2.0.2-py2.py3-none-any.whl (6.7 MB) Copy SHA256 Checksum SHA256 py2.py3 Wheel Jul 21, 2016
rabifier-2.0.2.tar.gz (6.7 MB) Copy SHA256 Checksum SHA256 Source Jul 21, 2016

Supported By

WebFaction WebFaction Technical Writing Elastic Elastic Search Pingdom Pingdom Monitoring Dyn Dyn DNS Sentry Sentry Error Logging CloudAMQP CloudAMQP RabbitMQ Heroku Heroku PaaS Kabu Creative Kabu Creative UX & Design Fastly Fastly CDN DigiCert DigiCert EV Certificate Rackspace Rackspace Cloud Servers DreamHost DreamHost Log Hosting