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Installation Guide

There are different options to install Arboreto.

Hint

It is highly recommended to prepare a Python environment with the Anaconda or Miniconda distribution and install Arboreto using the conda package manager.

This avoids complexities in ensuring that libraries like NumPy and SciPy link against an optimized implementation of linear algebra routines.

Install using conda (recommended)

The arboreto is available from bioconda, a distribution of bioinformatics software realized as a channel for the versatile conda package manager.

$ conda install -c bioconda arboreto

Install into a new conda environment

You can easily install arboreto into a fresh conda environment. See [1] for a better understanding of the how and what of Python environments.

Following code snippet creates a new conda environment called “arboreto-env” and installs arboreto and all its dependencies into that environment.

# create the conda environment named "arboreto-env"
$ conda create --name arboreto-env

# activate the conda environment we just created
$ source activate arboreto-env

# note: your terminal will indicate which environment is active on the left
(arboreto-env) $ ...

# install arboreto into the "arboreto-env" environment (hit Y to proceed)
(arboreto-env) $ conda install -c bioconda arboreto

When you’re done, deactivate the “arboreto-env” environment as follows:

# deactivate the current environment
(arboreto-env) $ source deactivate

# as you will see: the environment indication has disappeared.
$ ...

[1]	Why you need Python environments and how to manage them with Conda – Gergely Szerovay

Install using pip

The arboreto package is available from PyPI (Python Package Index), a repository of software for the Python programming language. Using pip, installing the arboreto package is straightforward:

$ pip install arboreto

Install from source

Installing Arboreto from source is possible using following steps:

1. clone the Github repository using the git tool:

$ git clone https://github.com/tmoerman/arboreto.git
$ cd arboreto

2. build Arboreto using the provided script:

$ ./pypi_build.sh

3. install the freshly built Arboreto package using pip:

$ pip install dist/*

Check out the installation

$ pip show arboreto

Name: arboreto
Version: 0.1.5
Summary: Scalable gene regulatory network inference using tree-based ensemble regressors
Home-page: https://github.com/tmoerman/arboreto
Author: Thomas Moerman
Author-email: thomas.moerman@gmail.com
License: BSD 3-Clause License
Location: /vsc-hard-mounts/leuven-data/software/biomed/Anaconda/5-Python-3.6/lib/python3.6/site-packages
Requires: scipy, scikit-learn, numpy, pandas, dask, distributed