Parses M.tuberculosis annotation (GFF file) and builds a Neo4j graph database storing the annotated features. tb2neo also aggregates and maps these annotated features to external services such as UniProt, CheMBL, DrugBank, KEGG, Reactome, QuickGo, STRING-DB etc.
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Instructions for a standalone Neo4j installation can be found here.
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Using Docker:
$ docker run -d -p 7474:7474 -p 7687:7687 --name neo -e NEO4J_AUTH=none -v=$HOME/neo4j/data:/data neo4j:3.5 ...
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Using
pip
:$ pip install -i https://test.pypi.org/simple/ tb2neo ...
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Using
setup
:Clone repository and create a virtual environment:
$ git clone https://github.com/COMBAT-TB/tb2neo.git ... $ cd tb2neo $ virtualenv envname $ source envname/bin/activate $ pip install -r requirements.txt $ python setup.py install
To load TB data, we use the H37Rv GFF3 file from EnsemblBacteria.
Run the following command to see available options
$ tb2neo --help
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Run the following command to load GFF features to Neo4j
$ tb2neo load_gff --gff_files PATH/TO/TB_GFF3_FILES
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Point your browser to localhost:7474.
db.schema()