BEAR: Better Emulation for Artificial Reads
Created by Stephen Johnson, Brett Trost, Dr. Jeffrey R. Long, Dr. Anthony Kusalik University of Saskatchewan, Department of Computer Science
BEAR is intended to be an easy-to-use collection of scripts for generating simulated WGS metagenomic reads with read lengths, quality scores, error profiles, and species abundances derived from real user-supplied WGS data.
BEAR is free for academic, non-commercial purposes. If you would like to use it for commercial purposes, please contact us.
BEAR is implemented as a collection of Perl and Python scripts, and is known to work with Perl v5.14.2 and Python v2.7.3. BEAR has the following dependencies:
-Perl Getopt::Long, Bio::SeqIO (part of BioPerl), List::Util modules
-Python Bio and Numpy packages
-Python sys, csv, StringIO, random, decimal, argparse modules
-DRISEE, which can be downloaded at https://github.com/MG-RAST/DRISEE
Instructions for installing BioPerl can be found at http://www.bioperl.org/wiki/Installing_BioPerl
Instructions for installing BioPython and Numpy can be found at http://biopython.org/wiki/Getting_Started and http://www.scipy.org/install.html respectively