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Gibbs -- a Package for Sequence Motif Discovery using Markov Chain Monte Carlo (MCMC) Sampling

Author: MH Seabolt (Github: @hseabolt)

This package creates a Perl object class representing a Gibbs sampler tailored for MCMC sampling of "mutually similar" motifs from string data. While written with biological sequences in mind, this package is also suitable for motif-finding from generic strings using any alphabet.

The Gibbs package is written in base Perl (v5.32.1).

Installation Instructions

The code can be obtained/installed in two ways:

  1. Install from Github:
git clone https://github.com/hseabolt/Gibbs.git
cd Gibbs
  1. Install from CPAN
# Using cpanm
cpanm gibbs

# Using the CPAN shell
perl -MCPAN -e shell
install gibbs
  1. Install using Conda (Bioconda)
conda install -c bioconda gibbs

If installing from Github, you can globally install the Gibbs.pm package by copying this file to a location that is visible to your PATH or Perl's @INC variables.

Running Instructions

An example script comes packaged with the Github version of this code which illustrates the basic idea of how to create and use the Gibbs object class for motif sampling. and can be plugged into any scripts running Perl.

License

This software is licensed under the MIT License. See also LICENSE.txt in this package's Git repo (https://github.com/hseabolt/Gibbs)

The MIT License

Copyright (c) 2022 Matthew H. Seabolt

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Citation

If you use this package in your work, please cite: Seabolt, MH. (2022). Gibbs: a Perl Package for Motif Discovery from Biological Sequences. In prep.