Package: py-graph-em
Graph Based Multi-Race EMPre-requisitesMake a virtual environment and activate it, runmake venvmakevenvsourcevenv/bin/activateInstall all the development dependencies. Will install packages from allrequirements-*.txtfiles.makeinstallData Directory StructureDonor files are indatadirectory, specified in the conf file.data
└── ct_mr_don_10.txtconf Directory StructureConfigure input/output directories and EM specific parameters.conf
└── minimal-configuration.jsonExample EM runRun thetest_emscript to produce frequences from the example data.python test_em.pyResults can be found inoutputdirectory.How to contribute:Fork the repository:https://github.com/nmdp-bioinformatics/py-graph-em.gitThis will create a new repository with the given name e.g.py-graph-em.Clone the repository locallygitclonehttps://github.com/pbashyal-nmdp/py-graph-em.gitcdpy-graph-emMake a virtual environment and activate it, runmake venv>makevenvpython3-mvenvvenv--promptpy-graph-em-venv=====================================================================Toactivatethenewvirtualenvironment,executethefollowingfromyourshellsourcevenv/bin/activateSource the virtual environmentsourcevenv/bin/activateDevelopment workflow is driven throughMakefile. Usemaketo list show all targets.> make
 clean                remove all build, test, coverage and Python artifacts
 clean-build          remove build artifacts
 clean-pyc            remove Python file artifacts
 clean-test           remove test and coverage artifacts
 lint                 check style with flake8
 behave               run the behave tests, generate and serve report
 pytest               run tests quickly with the default Python
 test                 run all(BDD and unit) tests
 coverage             check code coverage quickly with the default Python
 dist                 builds source and wheel package
 docker-build         build a docker image for the service
 docker               build a docker image for the service
 install              install the package to the active Python's site-packages
 venv                 creates a Python3 virtualenv environment in venv
 activate             activate a virtual environment. Run `make venv` before activating.Install all the development dependencies. Will install packages from allrequirements-*.txtfiles.makeinstallThe Gherkin Feature files, step files and pytest files go intestsdirectory:tests
|-- features
|   |-- algorithm
|   |   `-- SLUG\ Match.feature
|   `-- definition
|       `-- Class\ I\ HLA\ Alleles.feature
|-- steps
|   |-- HLA_alleles.py
|   `-- SLUG_match.py
`-- unit
    `-- test_my_project_template.pyPackage Module files go in themy_project_templatedirectory.my_project_template
|-- __init__.py
|-- algorithm
|   `-- match.py
|-- model
|   |-- allele.py
|   `-- slug.py
`-- my_project_template.pyRun all tests withmake testor different tests withmake behaveormake pytest.make behavewill generate report files and open the browser to the report.Usepython app.pyto run the Flask service app in debug mode. Service will be available athttp://localhost:8080/Usemake docker-buildto build a docker image using the currentDockerfile.make dockerwill build and run the docker image with the service.  Service will be available athttp://localhost:8080/The py-graph-em code was developed in theYOLO Laband at theNMDP. Please citeIsraeli, S., Gragert, L., Maiers, M., & Louzoun, Y. (2021). HLA haplotype frequency estimation for heterogeneous populations using a graph-based imputation algorithm. Human Immunology, 82(10), 746-757.‏=======
History0.0.1 (2021-08-25)First release on PyPI.