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Jorge Navarro edited this page Nov 22, 2024 · 15 revisions

BiG-SCAPE installation

⚪ Installation using conda

Download and decompress the current version of the code. In a terminal, this would be done with:

$ wget https://github.com/medema-group/BiG-SCAPE/archive/refs/tags/v1.1.9.zip
$ unzip BiG-SCAPE-1.1.9.zip

Although each library could be installed on its own, the use of a virtual environment is highly recommended. Here is a quick guide of BiG-SCAPE installation using Miniconda

Install Miniconda.

We recommend that you install the Python 3 version as default for all new conda environments.

$ wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
$ bash Miniconda3-latest-Linux-x86_64.sh

Create a new environment and install all the packages listed above using the environment.yml file (see additional documentation about conda here).

$ conda env create -f bigscape_dependencies.yml

Activate new environment (you should see a change in the prompt)

$ conda activate bigscape
(bigscape) $

Prepare the Pfam database

For simplicity, it will be put in the same BiG-SCAPE folder but it can be located elsewhere. BiG-SCAPE has been tested with versions 31 and 32, and newer versions should work fine. Note that in this example, version 32 is used. Browse the different versions here.:

(bigscape) $ cd BiG-SCAPE
(bigscape) $ wget https://ftp.ebi.ac.uk/pub/databases/Pfam/current_release/Pfam-A.hmm.gz && gunzip Pfam-A.hmm.gz 
(bigscape) $ hmmpress Pfam-A.hmm

Run BiG-SCAPE:

(bigscape) $ python bigscape.py --version

(see here for an overview of the options)

To deactivate the environment do source deactivate.

⚪ Docker (Linux-like systems)

If you use Docker, download the run_bigscape file from the repository using a web browser or from the command line:

$ curl -q https://raw.githubusercontent.com/medema-group/BiG-SCAPE/master/run_bigscape > run_bigscape

Then, change permissions to be able to execute the file, and run it:

$ chmod a+x run_bigscape
$ run_bigscape

⚪ Manual installation

If you don't (or can't) use conda, you will need to download all the files from the repository (e.g. from here, download and prepare the Pfam database (see above) and have the following packages installed in your system:

  • Python (BiG-SCAPE development will focus on Python 3. We will try to keep compatibility with Python 2 as long as we can)
  • The HMMER suite (3.1b2+)
  • The Pfam database
  • Biopython
  • Numpy
  • Fasttree
  • scipy
  • scikit-learn (tested with 0.19.1)
  • NetworkX (v2.x)
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