COMBAT-TB / tb2neo

A tool to aggregate and load TB data to Neo4j

tb2neo

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.

Usage

Neo4j Installation

• Instructions for a standalone Neo4j installation can be found here.

• 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
  ...

tb2neo Installation

• Using pip:

  $ pip install -i https://test.pypi.org/simple/ tb2neo
  ...

• 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

Loading TB Data

To load TB data, we use the H37Rv GFF3 file from EnsemblBacteria.

Run the following command to see available options

$ tb2neo --help
...

Run the following command to load GFF features to Neo4j

$ tb2neo load_gff --gff_files PATH/TO/TB_GFF3_FILES
...

Exploring TB data

Point your browser to localhost:7474.

db.schema()