3. installation guide

Bioconda (recommended)

Note, (for some setups at least) it is critical to specify the conda-forge channel before the bioconda channel to properly configure priority and lead to a successful installation.

Recommended: For a significantly faster installation process, use mamba in place of conda in the below commands, by installing mamba in your base conda environment.

# 1. install and activate lsabgc
# Note, panaroo is not a dependency by default due to difficulties 
# with passing bioconda's checks and space limitations in Azure
# when including it in the recipe
conda create -n lsabgc_env -c conda-forge -c bioconda lsabgc panaroo
conda activate lsabgc_env

# 2. setup annotation databases. This can take 5 - 30 
# minutes depending on whether you want to install the 
# small or full version of the databases and the end 
# product will be ~5 GB (small) or ~40 GB (full)! 

# Recommended for laptop: download small/minimal database 
# (only PGAP HMMs & MIBiG proteins)
setup_annotation_dbs.py -ld

# Recommended for server: download full database (PGAP, 
# CARD, KOfam, ISfinder, MIBiG, etc.)
setup_annotation_dbs.py

Note, when you create a conda environment using -n, the environment will typically be stored in your home directory. However, because the databases can be large (~40 GB), you might prefer to instead setup the conda environment somewhere else with more space on your system using -p. For instance, conda create -p /path/to/drive_with_more_space/lsabgc_conda_env/ -c conda-forge -c bioconda lsabgc. Then, next time around you would simply activate this environment by providing the path to it: conda activate /path/to/drive_with_more_space/lsabgc_conda_env/.

Docker via user-friendly wrapper script

We provide a Docker image containing lsaBGC-Pan, together with the minimal annotation databases (MIBiG + PGAP) on Dockerhub. The image is around ~13GB.

We also provide a wrapper bash script that makes using lsaBGC-Pan via Docker super easy.

# get wrapper script from GitHub
wget https://raw.githubusercontent.com/Kalan-Lab/lsaBGC-Pan/main/docker/run_lsaBGC-Pan.sh

# change permissions to allow execution
chmod a+x ./run_lsaBGC-Pan.sh

# run script
./run_lsaBGC-Pan.sh

See info on how to run run_lsaBGC-Pan.sh below.

Conda Manual

# 1. get the latest release (at the time of writing this, it was v1.0.6)
# but there might be newer releases.
wget https://github.com/Kalan-Lab/lsaBGC-Pan/archive/refs/tags/v1.0.6.tar.gz
tar -zxvf v1.0.6.tar.gz 
cd lsaBGC-Pan-1.0.6/

# 2. create conda environment using yaml file and activate it!
conda env create -f lsaBGC_env.yml -n lsaBGC_env
conda activate lsaBGC_env

# 3. complete python installation with the following commands:
pip install -e .

# 2. setup annotation databases. This can take 5 - 30 
# minutes depending on whether you want to install the 
# small or full version of the databases and the end 
# product will be ~5 GB (small) or ~40 GB (full)! 

# Recommended for laptop: download small/minimal database 
# (only PGAP HMMs & MIBiG proteins)
setup_annotation_dbs.py -ld

# Recommended for server: download full database (PGAP, 
# CARD, KOfam, ISfinder, MIBiG, etc.)
setup_annotation_dbs.py

Testing Installation

Testing Bioconda installation

You can test the installation worked by running the test dataset of 7 Cutibacterium acnes and Cutibacterium avidum genomes provided in this repo.

# get the input dataset
wget https://github.com/Kalan-Lab/lsaBGC-Pan/raw/main/test_case.tar.gz

# get the bash script to run the test
wget https://raw.githubusercontent.com/Kalan-Lab/lsaBGC-Pan/main/run_test.sh

# run the test!
bash run_test.sh

Testing Docker installation

You can test the installation worked by running the test dataset of 7 Cutibacterium acnes and Cutibacterium avidum genomes provided in this repo.

# get the input dataset
wget https://github.com/Kalan-Lab/lsaBGC-Pan/raw/main/test_case.tar.gz

# uncompress test_case.tar.gz and change in to the directory
rm test_case.tar.gz
wget https://github.com/Kalan-Lab/lsaBGC-Pan/raw/main/test_case.tar.gz
rm -rf test_case/
tar -zxvf test_case.tar.gz
cd test_case/

# get the wrapper bash script for Docker based running of 
# lsaBGC-Pan from GitHub
wget https://raw.githubusercontent.com/Kalan-Lab/lsaBGC-Pan/main/docker/run_lsaBGC-Pan.sh

# change permissions for it to allow execution
chmod a+x ./run_lsaBGC-Pan.sh

# run test
./run_lsaBGC-Pan.sh -g input_genomes/ -o lsabgc_pan_results/ -nb -c 4