<commit_before>CloudBioLinux is a build and deployment system which installs an easily
customizable selection of bioinformatics and machine learning libraries on a
linux container, bare virtual machine (VM) image, freshly installed PC, or in
the cloud. CloudBioLinux is a curated and community developed set of
instructions for tools provided by operating system packages (debs and RPMs),
external packaging efforts (`bioconda <https://bioconda.github.io/>`_ and
`homebrew-science <https://github.com/Homebrew/homebrew-science>`_)
and language specific library installers (Python, R, Perl and Ruby).

CloudBioLinux included software packages are fully customizable. In
addition to the default configuration, we support custom configuration
builds through flavors. Flavors support overriding default package
installations, making it simple to create derived installs for specific
purposes.

CloudBioLinux is a single install route for `Docker containers <http://www.docker.com/>`_
,desktop VMs such as `VirtualBox <http://digitizor.com/2011/01/07/virtualbox-4-0-install-ubuntu/>`_,
cloud providers such as `Amazon EC2 <http://aws.amazon.com/ec2/>`_ or
desktop machines. This works equally well for other virtual machines and
private cloud environments, including `XEN <http://xen.org/>`_, Linux
`KVM <http://www.linux-kvm.org/>`_,
`Eucalyptus <http://open.eucalyptus.com/>`_ and
`Openstack <http://www.openstack.org/>`_.

Quick start
===========

`bcbio <http://bcbio-nextgen.readthedocs.io/en/latest/>`_ uses CloudBioLinux as
the basis for tool installation and provides a large set of supported and tested
tools. If you're looking to bootstrap a system with tools and data for high
throughput sequencing analysis, we suggest using the `bcbio installer
<http://bcbio-nextgen.readthedocs.io/en/latest/contents/installation.html#automated>`_
which fully wraps CloudBioLinux and provides an easy path to customize install
directories, organisms and biological data installed.

We recommend using, or developing, a custom flavor to choose tools of interest
to install. The amount of bioinformatics software continues to increase -- there are
`over 1000 recipes in bioconda <https://github.com/bioconda/bioconda-recipes>`_
-- and it's difficult to come up with a default installation that includes
everything for everyone. The ``ngs_pipeline_minimal`` flavor has the set of NGS
analysis tools installed with bcbio and is a good starting point for
understanding the CloudBioLinux install process::

    fab -f fabfile.py -H localhost install_biolinux:flavor=ngs_pipeline_minimal

Installing CloudBioLinux on a local machine
===========================================

The install process for CloudBioLinux is fully automated through a `Fabric build
file <http://fabfile.org/>`_ written in Python. Everything is fully configurable
through plain text YAML configuration files, and custom build targets allow
installation of a subset of the total available packages.

Setup
-----

Retrieve the CloudBioLinux code base and install fabric::

    pip install fabric
    git clone git://github.com/chapmanb/cloudbiolinux.git
    cd cloudbiolinux<commit_msg>Improve quick start for conda-based installs<commit_after>CloudBioLinux is a build and deployment system which installs an easily
customizable selection of bioinformatics and machine learning libraries on a
linux container, bare virtual machine (VM) image, freshly installed PC, or in
the cloud. CloudBioLinux is a curated and community developed set of
instructions for tools provided by operating system packages (debs and RPMs),
external packaging efforts (`bioconda <https://bioconda.github.io/>`_ and
`homebrew-science <https://github.com/Homebrew/homebrew-science>`_)
and language specific library installers (Python, R, Perl and Ruby).

CloudBioLinux included software packages are fully customizable. In
addition to the default configuration, we support custom configuration
builds through flavors. Flavors support overriding default package
installations, making it simple to create derived installs for specific
purposes.

CloudBioLinux is a single install route for `Docker containers <http://www.docker.com/>`_
,desktop VMs such as `VirtualBox <http://digitizor.com/2011/01/07/virtualbox-4-0-install-ubuntu/>`_,
cloud providers such as `Amazon EC2 <http://aws.amazon.com/ec2/>`_ or
desktop machines. This works equally well for other virtual machines and
private cloud environments, including `XEN <http://xen.org/>`_, Linux
`KVM <http://www.linux-kvm.org/>`_,
`Eucalyptus <http://open.eucalyptus.com/>`_ and
`Openstack <http://www.openstack.org/>`_.

Quick start
===========

`bcbio <http://bcbio-nextgen.readthedocs.io/en/latest/>`_ uses CloudBioLinux as
the basis for tool installation and provides a large set of supported and tested
tools. If you're looking to bootstrap a system with tools and data for high
throughput sequencing analysis, we suggest using the `bcbio installer
<http://bcbio-nextgen.readthedocs.io/en/latest/contents/installation.html#automated>`_
which fully wraps CloudBioLinux and provides an easy path to customize install
directories, organisms and biological data installed.

We recommend using, or developing, a custom flavor to choose tools of interest
to install. The amount of bioinformatics software continues to increase -- there are
`over 1000 recipes in bioconda <https://github.com/bioconda/bioconda-recipes>`_
-- and it's difficult to come up with a default installation that includes
everything for everyone. The ``ngs_pipeline_minimal`` flavor has the set of NGS
analysis tools installed with bcbio and is a good starting point for
understanding the CloudBioLinux install process. To install inside an isolated
conda environment on a bare machine do::

    git clone https://github.com/chapmanb/cloudbiolinux.git
    cd cloudbiolinux
    wget https://repo.continuum.io/miniconda/Miniconda2-latest-Linux-x86_64.sh
    bash Miniconda2-latest-Linux-x86_64.sh -b -p ~/cblenv
    ~/cblenv/bin/conda install -y -c bioconda -c conda-forge pip fabric pyyaml
    ~/cblenv/bin/fab -f fabfile.py -H localhost install_biolinux:flavor=ngs_pipeline_minimal --set keep_isolated=true

Installing CloudBioLinux on a local machine
===========================================

The install process for CloudBioLinux is fully automated through a `Fabric build
file <http://fabfile.org/>`_ written in Python. Everything is fully configurable
through plain text YAML configuration files, and custom build targets allow
installation of a subset of the total available packages.

Setup
-----

Retrieve the CloudBioLinux code base and install fabric::

    pip install fabric
    git clone git://github.com/chapmanb/cloudbiolinux.git
    cd cloudbiolinux
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