A small software pipeline for the discovery of potentially new ECF σ factors and the prediction of their functionality with regards to the new classification schema (Casas-Pastor et al.).
Please install hmmer 3. Furthermore, you need to install the following python packages
# requirements.txt numpy biopython==1.78
python3 -m pip install -r requirements.txt
As a command line tool
You can install
ecf_classify with the ruby package manager
gem install ecf_classify
As a Ruby module
Add this line to your application's Gemfile:
And then execute:
Or install it yourself as:
$ bundle install $ rake install
ecf_classify commands: ecf_classify --version # print the version ecf_classify groups [FILE] # Classifies protein sequences into ECF groups ecf_classify help [COMMAND] # Describe available commands or one specific command ecf_classify subgroups [FILE] # Classifies protein sequences into ECF subgroups Options: -h, [--help], [--no-help]
Usage: ecf_classify groups [FILE] Options: -p, [--probabilities=PROBABILTIES] -h, [--help], [--no-help] Classifies protein sequences into ECF groups
Usage: ecf_classify subgroups [FILE] Options: -p, [--probabilities=PROBABILTIES] -h, [--help], [--no-help] Classifies protein sequences into ECF subgroups
After checking out the repo, run
bin/setup to install dependencies. Then, run
rake spec to run the tests. You can also run
bin/console for an interactive prompt that will allow you to experiment.
To install this gem onto your local machine, run
bundle exec rake install. To release a new version, update the version number in
version.rb, and then run
bundle exec rake release, which will create a git tag for the version, push git commits and tags, and push the
.gem file to rubygems.org.
Bug reports and pull requests are welcome on GitHub at https://github.com/r-mllr/ecf_classify.
Publication / How to cite
Casas-Pastor D, Müller RR, Jaenicke S, Brinkrolf K, Becker A, Buttner MJ, Gross CA, Mascher T, Goesmann A, Fritz G. Expansion and re-classification of the extracytoplasmic function (ECF) σ factor family. Nucleic Acids Res. 2021 Jan 4:gkaa1229. doi: 10.1093/nar/gkaa1229. Epub ahead of print. PMID: 33398323.
The gem is available as open source under the terms of the GPL-3.