Perl module to take in an genomic assembly and produce annoation
Bio-AutomatedAnnotation is a Perl module that takes in a genomic assembly and produces annoation. The underlying software is Prokka.
Bio-AutomatedAnnotation has the following dependencies:
There are a number of ways to install Bio-AutomatedAnnotation and details are provided below. If you encounter an issue when installing Bio-AutomatedAnnotation please contact your local system administrator. If you encounter a bug please log it here or email us at path-help@sanger.ac.uk.
Install cpanminus:
apt-get install cpanminus
Then install Bio::AutomatedAnnotation:
cpanm Bio::AutomatedAnnotation
Install conda. Then install bioconda and perl-bio-automatedannotation:
conda config --add channels r
conda config --add channels defaults
conda config --add channels conda-forge
conda config --add channels bioconda
conda install perl-bio-automatedannotation
Clone the repository:
git clone https://github.com/sanger-pathogens/Bio-AutomatedAnnotation.git
Move into the directory and install all dependencies using DistZilla:
cd Bio-AutomatedAnnotation
dzil authordeps --missing | cpanm
dzil listdeps --missing | cpanm
./install_dependencies.sh
Run the tests:
dzil test
If the tests pass, install pipelines_reporting:
dzil install
The test can be run with dzil from the top level directory:
dzil test
Automated annotation of assemblies:
use Bio::AutomatedAnnotation;
my $obj = Bio::AutomatedAnnotation->new(
assembly_file => $assembly_file,
annotation_tool => $annotation_tool,
sample_name => $lane_name,
accession_number => $accession,
dbdir => $dbdir,
tmp_directory => $tmp_directory
);
$obj->annotate;
Bio-AutomatedAnnotation is free software, licensed under GPLv3.
Please report any issues to the issues page or email path-help@sanger.ac.uk.
If you use this software please cite:
Prokka: rapid prokaryotic genome annotation.
Seemann T., Bioinformatics. 2014 Jul 15;30(14):2068-9. doi: 10.1093/bioinformatics/btu153. Epub 2014 Mar 18.
Robust high throughput prokaryote de novo assembly and improvement pipeline for Illumina data
Page AJ, De Silva, N., Hunt M, Quail MA, Parkhill J, Harris SR, Otto TD, Keane JA, Microbial Genomics, 2016. doi: 10.1099/mgen.0.000083