Metadata-Version: 2.1
Name: edge-genome
Version: 3.1.3
Summary: Genome Engineering Tool
Home-page: https://github.com/ginkgobioworks/edge/
Author: Ginkgo Bioworks
Author-email: devs@ginkgobioworks.com
License: MIT
Keywords: edge genome annotate track query django database ginkgo
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Web Environment
Classifier: Environment :: Other Environment
Classifier: Framework :: Django :: 1.6
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: JavaScript
Classifier: Programming Language :: SQL
Classifier: Topic :: Database
Classifier: Topic :: Internet :: WWW/HTTP :: Indexing/Search
Classifier: Topic :: Internet :: WWW/HTTP :: WSGI :: Application
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Artificial Life
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Text Processing :: General
License-File: LICENSE.txt

====
Edge
====

.. image:: https://travis-ci.org/ginkgobioworks/edge.svg?branch=master
    :target: https://travis-ci.org/ginkgobioworks/edge

Edge keeps structural changes between a genome and child genomes derived
from it. A user creates a modified genome by applying a sequence-based
operation, such as homologous recombination, to a parent genome. Users
can annotate or make corrections to sequences on a genome; Edge
automatically applies the changes to the appropriate regions on the
derived genomes. Edge does this efficiently: making a change on a parent
genome takes O(1) and is automatically propagated to the modified
genomes.

Edge uses O(D) amount of storage for each modified genome, where D is
the number of differences between a modified genome and its parent. The
current implementation additionally keeps a cache of annotations to base
pair numbers, but this cache is soft-data and is invalidated and
re-built on demand.

A modified genome can be re-created by re-applying operations to a new
genome (think git rebase). Currently, however, annotating a genome is
not an operation. Also, applying the same operation to a genome twice
results in a single child genome, not two.

Edge provides UIs to look at operations and changes and APIs for making
changes. Edge can export genome sequences and annotations as GFF files.
While Edge comes with a simple UI for browsing features and sequences,
the UI is primitive compared to other specialized applications.


Try it using Docker
-------------------
* Use ``docker-compose``:

The Docker environment is defined in ``docker-compose.yml``. Use the ``edge`` service for your
commands.

To start the edge server:

::

    docker-compose up

Then check it out in your browser: http://localhost:9000/edge/#/genomes .

To import a genome, use:

::

    docker-compose run edge python src/manage.py import_gff 'Saccharomyces cerevisiae' example/sc_s288c.gff

To run a shell inside the Edge container:

::

    docker-compose run --rm edge bash

* Alternatively, you can use the ``Makefile``:

The ``Makefile`` holds all the commands necessary for managing the server and database, both in
usage and development. Run ``make`` without arguments to see a list of commmands.

Any of these ``make`` targets can be run directly from a shell inside a container:

::

    you@localhost:edge$ docker-compose run --rm edge bash
    # Now you're inside the Docker container
    root@docker-image:/usr/src/edge# make test

Furthermore, any target can have ``-ext`` added to it. Commands that end in ``-ext`` are meant to be
run *externally* to the image, *i.e.*, from the host system.

For example, to start the edge server:

::

    make start-ext


To run a shell:

::

    make bash-ext


To import a genome as an example:

::

    make add-s288c-ext


If the edge app is already running in a container, or you don't want to rebuild the image yet, you
can change ``-ext`` to ``-ext_fast``, which will run the make target in a new container without
trying to rebuild the image.


Try it without Docker
---------------------

On your own machine, Construct your virtual environment and pip-install dependencies (use
``requirements.txt``).

To start a server, first update ``src/server/settings.py`` to use either sqlite or MySQL. For MySQL,
create the appropriate databse. Then,

::

    make migrate
    (cd example; gunzip ecoli-mg1655.gff.gz; gunzip yeast.gff.gz)
    python src/manage.py import_gff 'E. coli MG1655' example/ecoli-mg1655.gff
    python src/manage.py import_gff 'Saccharomyces cerevisiae' example/yeast.gff
    make run

Then set your browser to http://localhost:8000/edge/. Note the port is different than the Docker
case

If you need `NCBI BLAST`_ or Primer3_ support, you'll need to make sure the packages are installed
on your system. Debian and Ubuntu distributions provide binary versions of both of these packages.

Depending on where the NCBI BLAST tools and Primer3 are installed, you will probably need to tell
edge where to find them, using the following environment variables:

::

    NCBI_BIN_DIR       # Path to directory holding ncbi binaries, e.g. /usr/bin
    PRIMER3_BIN        # Path to primer3 binary, e.g. /usr/bin/primer3_core
    PRIMER3_CONFIG_DIR # Path to primer3 config directory, e.g. etc/primer3_config/


Then, to set up the edge BLAST db, from the ``src`` subdirectory,

::

    python manage.py build_edge_blastdb

.. _NCBI BLAST: https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastDocs&DOC_TYPE=Download
.. _Primer3: https://sourceforge.net/projects/primer3/


Editing data
------------

You can edit genome and fragment metadata, such as name, notes, circular attributes, from the Django
admin. Create a Django admin superuser, (see the ``superuser`` make target), then set your browser
to the ``/admin/`` endpoint of wherever you are running your dev server.


Deploying to production
-----------------------

Do *not* use the Dockerfile as-is for production, or the ``make run`` task. Django's ``runserver``
command is not meant to run a production server. Instead, you'll need to spin up a production WSGI
server and run the Django projct with that, with your own settings. In this situation, it's better
to simply install the ``edge-genome`` python package on your deployed system and add it to your
deployment Django server's ``installed_apps`` setting. The package is designed so that, when built,
it already contains all of the javascript assets compiled in their final state.


Development, testing, and package release
-----------------------------------------

Running tests
~~~~~~~~~~~~~

When developing locally, you can run tests in the controlled environment of the docker container
from your local machine with ``make test-all-ext``. Make sure you've run the migrations at least once
before doing this. If your server is already running, and you want to run tests from the host
machine in a separate container, use ``make test-all-ext_fast``. Or just keep a container up and run
the tests from inside it.

Static files
~~~~~~~~~~~~

Note that edge uses webassets_ for compilation of static assets. These assets are not automatically
compiled (because the integration of that with Django is flaky). Instead, compile assets after
cahnging them with ``make build_assets``. To constantly recompile them, see ``make watch``.

Static dependencies are managed with Bower_. (Eventually to be replaced with npm_/webpack_).
Dependencies are downloaded before the python package is built so Python package consumers already
have all required JavaScript.

Versioning
~~~~~~~~~~

Edge is versioned semantically. Continuous integration builds are done automatically on all branches
through Travis CI, and tagged commits to master are automatically released to PyPI. To release a new
version, bump the version number with the appropriate severity of the changes (major, minor, or
patch), and push the resulting tagged commits to the GitHub remote repo:

::

    you@localhost:edge$ docker-compose run --rm edge make bump/patch-ext # Or bump/major, or bump/minor
    you@localhost:edge$ git push --tags origin master

If you cannot push to master directly, do the same thing on a new branch and submit a pull request.

.. _webassets: https://webassets.readthedocs.io/
.. _Bower: https://bower.io/
.. _npm: https://npmjs.org/
.. _webpack: https://webpack.js.org/


