Metadata-Version: 1.1
Name: edge-genome
Version: 0.4.2
Summary: Genome Engineering Tool
Home-page: https://github.com/ginkgobioworks/edge/
Author: Ginkgo Bioworks
Author-email: devs@ginkgobioworks.com
License: MIT
Description: 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
        -------------------
        
        ::
        
            make start-ext
        
        Then check it out in your browser: http://localhost:9000/edge/#/genomes
        
        Example: to import an genome, try
        
        ::
        
            make add-s288c-ext
        
        
        Or, if your app is already running, ``make add-s288c-ext_fast``, which will run the job without
        trying to rebuild the image.
        
        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.
        
        The Docker environment is defined in ``docker-compose.yml``. Ese the ``edge`` service for your
        commands.
        
        Of course, any of these ``make`` targets can be run directly from a shell inside a container from
        either service:
        
        ::
        
            you@localhost:edge$ docker-compose run --rm edge bash
            # Now you're inside the Docker container
            root@docker-image:/usr/src/edge# make test
        
        
        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.
        
        
        Development, testing, and package release
        -----------------------------------------
        
        When developing locally, you can run tests in the controlled environment of the docker container
        from your local machine with ``make test-ext.``
        
        Edge is versioned semantically. Continuous integration is 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$ make bump/patch-ext # Or bump/major, or bmp/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.
        
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
