Genome Engineering Tool
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:
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:
To run a shell:
To import a genome as an example:
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
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
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
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-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.
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.
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$ 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.
Release history Release notifications
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size & hash SHA256 hash help||File type||Python version||Upload date|
|edge_genome-1.1.0-py2-none-any.whl (2.6 MB) Copy SHA256 hash SHA256||Wheel||py2|
|edge-genome-1.1.0.tar.gz (2.4 MB) Copy SHA256 hash SHA256||Source||None|