COMBAT-TB-NeoDB: fostering tuberculosis research through integrative analysis using graph database technologies

Thoba Lose; Peter van Heusden; Alan Christoffels

doi:10.1093/bioinformatics/btz658

COMBAT-TB-NeoDB: fostering tuberculosis research through integrative analysis using graph database technologies

Bioinformatics. 2020 Feb 1;36(3):982-983. doi: 10.1093/bioinformatics/btz658.

Authors

Thoba Lose¹, Peter van Heusden¹, Alan Christoffels¹

Affiliation

¹ South African National Bioinformatics Institute, South African MRC Bioinformatics Unit, University of the Western Cape, Bellville, 7535, South Africa.

Abstract

Motivation: Recent advancements in genomic technologies have enabled high throughput cost-effective generation of 'omics' data from M.tuberculosis (M.tb) isolates, which then gets shared via a number of heterogeneous publicly available biological databases. Albeit useful, fragmented curation negatively impacts the researcher's ability to leverage the data via federated queries.

Results: We present Combat-TB-NeoDB, an integrated M.tb 'omics' knowledge-base. Combat-TB-NeoDB is based on Neo4j and was created by binding the labeled property graph model to a suitable ontology namely Chado. Combat-TB-NeoDB enables researchers to execute complex federated queries by linking prominent biological databases, and supplementary M.tb variants data from published literature.

Availability and implementation: The Combat-TB-NeoDB (https://neodb.sanbi.ac.za) repository and all tools mentioned in this manuscript are freely available at https://github.com/COMBAT-TB.

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Databases, Factual
Genome
Genomics
Humans
Mycobacterium tuberculosis*
Software
Tuberculosis*