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Update readme and misc deployment fixes.
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- Updated the README to restructure to be more in line with the current
  state of the project.
- Added instructions for deployment on Apache and Ubuntu.
- Updated the configuration interface to be more sensible in this
  context.
- Fixed deployment issue in which the index.html template was not being
  included in the tarball.
- Bumped version number to 0.1.0a2 to distinguish this version from the
  current PyPI package.
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@jeromekelleher
jeromekelleher committed Mar 12, 2015
1 parent cfc2fe5 commit 4847ab0
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3 changes: 2 additions & 1 deletion MANIFEST.in
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include README.txt
include ez_setup.py
include LICENSE
include LICENSE
include ga4gh/templates/*.html
342 changes: 217 additions & 125 deletions README.txt
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Expand Up @@ -39,10 +39,166 @@ Our aims for this implementation are:
for details). This allows for easy installation of the ``ga4gh`` reference code
across a range of operating systems.

*************************************
Configuration file and data hierarchy
*************************************

The GA4GH reference server is a `Flask application <http://flask.pocoo.org/>`_
and uses the standard `Flask configuration file mechanisms
<http://flask.pocoo.org/docs/0.10/config/>`_. An example configuration file
might look like::

DATA_SOURCE = "/path/to/data/root"
# TODO other example config

Data is input to the GA4GH server as a directory hierarchy, in which
the structure of data to be served is represented by the filesystem. For now,
we support only one dataset, but this will be generalised to multiple
datasets in later releases. An example data layout might be::

ga4gh-data/
/variants/
variantSet1/
chr1.vcf.gz
chr1.vcf.gz.tbi
chr2.vcf.gz
chr2.vcf.gz.tbi
# More VCFs
variantSet2/
chr1.bcf
chr1.bcf.csi
chr2.bcf
chr2.bcf.csi
# More VCFs
/reads/
readGroupSet1
# TODO fill in details for read data.

************
Installation
************

There are three different types of installation that we deal with here:
`Deployment`_, `Client tools`_ and `Development`_ installations. A
deployment installation is a production server, usually using Apache
or another web server on a dedicated machine. A client tools installation
creates a sandbox in which a user can easily try out the GA4GH client
utilities, and run queries against arbitrary servers (specifically,
any server running the correct version of the GA4GH API; not necessarily
this implementation). Finally, a development installation is a local
installation used for either development of GA4GH reference server itself,
or client applications depending on the reference Python client libraries.

----------
Deployment
----------

To deploy on Apache on Debian/Ubuntu platforms, do the following.

- Install some basic pre-requisite packages::

$ sudo apt-get install python-dev zlib1g-dev libdb-dev

- Install Apache and mod_wsgi, and enable mod_wsgi::

$ sudo apt-get install apache2 libapache2-mod-wsgi
$ sudo a2enmod wsgi

- Create the python egg cache directory, and make it writable by
www-data::

$ sudo mkdir /var/cache/apache2/python-egg-cache
$ sudo chown www-data:www-data /var/cache/apache2/python-egg-cache/

- Create a directory to hold the GA4GH server code, configuration
and data. For convenience, we make this owned by the current user
(but make sure all the files are world-readable).::

$ sudo mkdir /srv/ga4gh
$ sudo chown $USER /srv/ga4gh
$ cd /srv/ga4gh

- Make a virtualenv, and install the ga4gh package::

$ virtualenv ga4gh-server-env
$ source ga4gh-server-env/bin/activate
$ pip install --pre ga4gh # We need the --pre because ga4gh is pre-release
$ deactivate

- Download and unpack the example data::

$ wget http://www.well.ox.ac.uk/~jk/ga4gh-example-data.tar.gz
$ tar -zxf ga4gh-example-data.tar.gz

- Create the WSGI file at ``/srv/ga4gh/application.wsgi`` and write the following
contents::

from ga4gh.frontend import app as application
import ga4gh.frontend as frontend
frontend.configure("/srv/ga4gh/config.py")

- Create the configuration file at ``/srv/ga4gh/config.py``, and write the
following contents::

DATA_SOURCE = "/srv/ga4gh/ga4gh-example-data"

*******************************
Installing the reference server
*******************************
- Configure Apache. Edit the file ``/etc/apache2/sites-enabled/000-default.conf``
and insert the following contents towards the end of the file
(*within* the ``<VirtualHost:80>...</VirtualHost>`` block)::

WSGIDaemonProcess ga4gh python-path=/srv/ga4gh/ga4gh-server-env/lib/python2.7/site-packages python-eggs=/var/cache/apache2/python-egg-cache
WSGIScriptAlias /ga4gh /srv/ga4gh/application.wsgi

<Directory /srv/ga4gh>
WSGIProcessGroup ga4gh
WSGIApplicationGroup %{GLOBAL}
Require all granted
</Directory>

- Restart Apache::

$ sudo service apache restart

- Test the installation by pointing a web-browser at the root URL; for example,
to test on the installation server use::

$ links http://localhost/ga4gh

To test the API, make a development installation and try running some
`Example client queries`_ against the server

These instructions are just one way in which we can achieve the same thing.
There are any number of different ways in which we can set up a WSGI
application under Apache, which may be preferable in different installations.
(In particular, the Apache configuration here may be specific to
Ubuntu 14.04, where this was tested.)
See the `mod_wsgi documentation <https://code.google.com/p/modwsgi/>` for
more details. These instructions are also specific to Debian/Ubuntu and
different commands and directory structures will be required on
different platforms.

The server can be deployed on any WSGI compliant web server. See the
instructions in the `Flask documentation
<http://flask.pocoo.org/docs/0.10/deploying/>` for more details on
how to deploy on various other servers.

+++++++++++++++
Troubleshooting
+++++++++++++++

If you are encountering difficulties getting the above to work, it is helpful
to turn on debugging output. Do this by adding the following line to your
config file::

DEBUG = True

When an error occurs, the details of this will then be printed to the web server's
error log (in Apache on Debian/Ubuntu, for example, this is ``/var/log/apache2/error.log``).


------------
Client tools
------------

Prerequisites:

Expand All @@ -59,7 +215,8 @@ General installation procedure:
* (On MacOS X, make sure the LDFLAGS and CFLAGS environment variables are set to
include the lib and include directories for the Berkeley DB install of your choice.
The wormtable help page cited above provides more detailed instructions, or
see the `Appendix`_ to this README for an example install on that platform.)
see the `System specific install examples`_ section for an example install
on that platform.)

* Create a python sandbox directory using virtualenv, preferably
*not* inside the ga4gh server directory. For an good introduction
Expand Down Expand Up @@ -87,32 +244,8 @@ General installation procedure:

A successfull install should result in a clean run of all the tests,
resulting in a line of dots followed by ``OK``. If this still isn't working,
you may want to check the `Appendix`_ at the end of this README for
system-specific installation examples.

********************************
Serving variants from a VCF file
********************************

Two implementations of the variants API are available that can serve data based
on existing VCF files. These backends are based on tabix and `wormtable
<http://www.biomedcentral.com/1471-2105/14/356>`_, which is a Python library to
handle large scale tabular data. See `Wormtable backend`_ for instructions on
serving VCF data from the GA4GH API.

*****************
Wormtable backend
*****************

The wormtable backend allows us to serve variants from an arbitrary VCF file.
The VCF file must first be converted to wormtable format using the ``vcf2wt``
utility (the `wormtable tutorial
<http://pythonhosted.org/wormtable/tutorial.html>`_ discusses this process).
A subset (1000 rows for each chromosome) of the 1000 Genomes VCF data (20110521
and 20130502 releases) has been prepared and converted to wormtable format
and made available `here <http://www.well.ox.ac.uk/~jk/ga4gh-example-data.tar.gz>`_.
See `Converting 1000G data`_ for more information on converting 1000 genomes
data into wormtable format.
you may want to check the `System specific install examples`_ section.


To run the server on this example dataset, follow the steps on
installing the server, then download and unpack the example data ::
Expand All @@ -125,10 +258,22 @@ script, which will do these steps for you::

$ python scripts/update_data.py

You can now run the server, telling it to serve variants from the sets in
You can now run the server, which will by default serve variants from the sets in
the downloaded datafile::

$ ga4gh_server ga4gh-example-data
$ ga4gh_server

To change the data that is served, a configuration file can be specified using
the ``-f <config_file>`` command line argument. Run::

$ ga4gh_server --help

for details on the options for this program.


++++++++++++++++++++++
Example client queries
++++++++++++++++++++++

To run queries against this server, we can use the ``ga4gh_client`` program;
for example, here we run the ``variants/search`` method over the
Expand All @@ -142,101 +287,11 @@ has variant name ``rs75454623``::

$ ga4gh_client variants-search http://localhost:8000/v0.5.1 -V 1000g_2013.wt -r 1 -n rs75454623 | less -S

+++++++++++++++++++++
Converting 1000G data
+++++++++++++++++++++

To duplicate the data for the above example, we must first create VCF files
that contain the entire variant set of interest. The VCF files for the set
mentioned above have been made `available
<http://www.well.ox.ac.uk/~jk/ga4gh-example-source.tar.gz>`_. After downloading
and extracting these files, we can build the wormtable using ``vcf2wt``::

$ vcf2wt 1000g_2013-subset.vcf -s schema-1000g_2013.xml -t 1000g_2013

Schemas for the 2011 and 2013 1000G files have been provided as these do a
more compact job of storing the data than the default auto-generated schemas.
We must also truncate and remove some columns because of a current limitation
in the length of strings that wormtable can handle.
After building the table, we must create indexes on the ``POS`` and ``ID`` columns::

$ wtadmin add 1000g_2013 CHROM+POS
$ wtadmin add 1000g_2013 CHROM+ID

The ``wtadmin`` program supports several
commands to administer and examine the dataset; see ``wtadmin help`` for details.
These commands and schemas also work for the full 1000G data; however, it is
important to specify a sufficiently large `cache size
<http://pythonhosted.org/wormtable/performance.html#cache-tuning>`_ when
building and indexing such large tables.

*************
Tabix backend
*************

The tabix backend allows us to serve variants from an arbitrary VCF file. The
VCF file must first be indexed with `tabix
<http://samtools.sourceforge.net/tabix.shtml>`_. Many projects, including the
`1000 genomes project
<http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20130502/>`_, release files
with tabix indices already precomputed. This backend can serve such datasets
without any preprocessing via the command::

$ ga4gh_server DATADIR

where DATADIR is a directory that contains subdirectories of tabix-indexed VCF
file(s). There cannot be more than one VCF file in any subdirectory that has
data for the same reference contig.

******
Layout
******

The code for the project is held in the ``ga4gh`` package, which corresponds to
the ``ga4gh`` directory in the project root. Within this package, the
functionality is split between the ``client``, ``server``, ``protocol`` and
``cli`` modules. The ``cli`` module contains the definitions for the
``ga4gh_client`` and ``ga4gh_server`` programs.

For development purposes, it is useful to be able to run the command line
programs directly without installing them. To do this, use the
``server_dev.py`` and ``client_dev.py`` scripts. (These are just shims to
facilitate development, and are not intended to be distributed. The
distributed versions of the programs are packaged using the setuptools
``entry_point`` key word; see ``setup.py`` for details). For example, the run
the server command simply run::

$ python server_dev.py
usage: server_dev.py [-h] [--port PORT] [--verbose] {help,wormtable,tabix} ...
server_dev.py: error: too few arguments

++++++++++++
Coding style
++++++++++++

The code follows the guidelines of `PEP 8
<http://legacy.python.org/dev/peps/pep-0008>`_ in most cases. The only notable
difference is the use of camel case over underscore delimited identifiers; this
is done for consistency with the GA4GH API. Code should be checked for compliance
using the `pep8 <https://pypi.python.org/pypi/pep8>`_ tool.


**********
Deployment
**********

*TODO* Give simple instructions for deploying the server on common platforms
like Apache and Nginx.

Configuration parameters are specified in the file ga4gh/server/config.py;
they can be overridden by setting the absolute path of a file containing
new values in the environment variable GA4GH_CONFIGURATION.

********
Appendix
********

**system specific install examples**
++++++++++++++++++++++++++++++++
System specific install examples
++++++++++++++++++++++++++++++++

MacOS X (with MacPorts)::

Expand All @@ -253,4 +308,41 @@ MacOS X (with MacPorts)::
*TODO* Append examples of installs (using package managers if possible, no dependency
installs from source) on the target platform of your choice.

-----------
Development
-----------

A development installation of the GA4GH reference implementation is a local
copy of the ``server`` repo, along with all of the tools required for development.
Please ensure that all the system requirements (as listed above) are installed, and
clone a local copy of the repo. Install all of the required Python libraries
into your Python user installation::

$ pip install -r requirements.txt --user

All of the command line interface utilities have local scripts
that simplify development: for example, we can run the local version of the
``ga2sam`` program by using::

$ python ga2sam_dev.py

To run the server locally in development mode, we can use the ``server_dev.py``
script, e.g.::

$ python server_dev.py

will run a server using the default configuration. This default configuration
expects a data hierarchy to exist in the ``ga4gh-example-data`` directory.
This default configuration can be changed by providing a (fully qualified)
path to a configuration file (see the `Configuration file and data hierarchy`_
section for details).

++++++
Layout
++++++

The code for the project is held in the ``ga4gh`` package, which corresponds to
the ``ga4gh`` directory in the project root. Within this package, the
functionality is split between the ``client``, ``server``, ``protocol`` and
``cli`` modules. The ``cli`` module contains the definitions for the
``ga4gh_client`` and ``ga4gh_server`` programs.
2 changes: 1 addition & 1 deletion ga4gh/__init__.py
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Expand Up @@ -2,4 +2,4 @@
Reference implementation of the GA4GH APIs.
"""

__version__ = '0.1.0a1'
__version__ = '0.1.0a2'
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