antaRNA - Ant Colony Optimized RNA Sequence Design

antaRNA applies the principle of Ant Colony optimization (ACO) to the problem of inverse folding a RNA structure i.e. finding a suitable sequence, which can fold into that structure. Besides the structural constraint, antaRNA realizes the usage of sequence constraints and provides the user to specify a GC value constraint.

Requirements

• For the usage of antaRNA, the program RNAfold of the ViennaRNA Package version 2.1.3 are required. They need to be listed in the PATH variable of the system.
• For the usage of pseudoknot structure constraint, pKiss_mfe is required to be installed on the machine, such that regular calls of it can be executed.
• Python should be installed. Required is at least version 2.7.3
• You need some non standard python libraries to execute antaRNA. So far it is only:
  • numpy

Download a provided python file of antaRNA and save it to your favorite place. Go and execute!

antaRNA project repository on GitHub.

Direct .py downloads:

• antaRNA_v109.py
  • Submission Version, subject to the main manuscript
• antaRNA_v113.py
  • Submission Version, subject to the pseudoknot/webserver manuscript.
• antaRNA_v114.py
  • Revised Submission Version, subject to the pseudoknot/webserver manuscript.

antaRNA is available through the Freiburg RNA Tools

antaRNA is available through the RNA-workbench Docker Image which is part of the Galaxy Docker Image.

Users, which already host a Galaxy Instance, antaRNA can be obtained through its repository.

Once downloaded and having installed all dependencies, you can execute antaRNA from the shell.
Optional you can also include the the program to your PYTHONPATH, so that you can use antaRNA from within python or call functions from other python scripts.

Example for generating a sequence wild-card constrained instances comprising a desired target GC-content of 50%:

python antaRNA_vX.py -Cstr "....(((((...)))))...(((((...)))))..." -tGC 0.5

In order to use the pseudoknot option within antaRNA, the flags -p and -pkPar have to be used.

Example for generating a sequence wild-card constrained instances comprising a desired target GC-content of 50% using pkiss as folding prediction and using the parametrized parameters for pseudoknots:

python antaRNA_vX.py -Cstr "....(((((.[[[[.))))).........]]]]..." -tGC 0.5 -p -pkPar

A regular call of antaRNA will produce an output in classical FASTA format: A header and the output sequence of the program.

The option -v, however, induces a three lined verbose output: In the first line some stats about the run and qualities of the result are added; in the second line the solution structure is listed; in the third line, the solution sequence is listed:

RFAM v.11.0 dataset: [training] and [test]

Pseudobase++ dataset (as of 2014/12): [training] and [test]

GC Management

GC target Value Handling

Terrain Graph

Terrain Vertices' and Edges' Features
Terrain Initialization
Structure/Sequence Constraint Dependent Terrain Modification
GC Constraint Dependent Terrain Modification

Miscellaneous

IUPAC Nucleotide Definition

Help

antaRNA Variables or type python antaRNA_vX.py -h

If you employ antaRNA in your work, please cite:

• Robert Kleinkauf, Martin Mann and Rolf Backofen
  antaRNA - Ant Colony Based RNA Sequence Design
  Published Online: May,27 2015 in Bioinformatics;
  
• Robert Kleinkauf, Torsten Houwaart, Rolf Backofen and Martin Mann
  antaRNA - Multi-Objective Inverse Folding of Pseudoknot RNA using Ant-Colony Optimization
  Submitted July 2015