» Articles » PMID: 28302555

Development of Bioinformatics Infrastructure for Genomics Research

Abstract

Background: Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet's role has evolved in response to changing needs from the consortium and the African bioinformatics community.

Objectives: H3ABioNet set out to develop core bioinformatics infrastructure and capacity for genomics research in various aspects of data collection, transfer, storage, and analysis.

Methods And Results: Various resources have been developed to address genomic data management and analysis needs of H3Africa researchers and other scientific communities on the continent. NetMap was developed and used to build an accurate picture of network performance within Africa and between Africa and the rest of the world, and Globus Online has been rolled out to facilitate data transfer. A participant recruitment database was developed to monitor participant enrollment, and data is being harmonized through the use of ontologies and controlled vocabularies. The standardized metadata will be integrated to provide a search facility for H3Africa data and biospecimens. Because H3Africa projects are generating large-scale genomic data, facilities for analysis and interpretation are critical. H3ABioNet is implementing several data analysis platforms that provide a large range of bioinformatics tools or workflows, such as Galaxy, the Job Management System, and eBiokits. A set of reproducible, portable, and cloud-scalable pipelines to support the multiple H3Africa data types are also being developed and dockerized to enable execution on multiple computing infrastructures. In addition, new tools have been developed for analysis of the uniquely divergent African data and for downstream interpretation of prioritized variants. To provide support for these and other bioinformatics queries, an online bioinformatics helpdesk backed by broad consortium expertise has been established. Further support is provided by means of various modes of bioinformatics training.

Conclusions: For the past 4 years, the development of infrastructure support and human capacity through H3ABioNet, have significantly contributed to the establishment of African scientific networks, data analysis facilities, and training programs. Here, we describe the infrastructure and how it has affected genomics and bioinformatics research in Africa.

Citing Articles

Cohort Profile: Africa Wits-INDEPTH partnership for Genomic studies (AWI-Gen) in four sub-Saharan African countries.

Tluway F, Agongo G, Baloyi V, Boua P, Kisiangani I, Lingani M Int J Epidemiol. 2025; 54(1).

PMID: 39899987 PMC: 11790221. DOI: 10.1093/ije/dyae173.


Challenges and opportunities of developing bioinformatics platforms in Africa: the case of BurkinaBioinfo at Joseph Ki-Zerbo University, Burkina Faso.

Tibiri E, Boua P, Soulama I, Dubreuil-Tranchant C, Tando N, Tollenaere C Brief Bioinform. 2025; 26(1).

PMID: 39899597 PMC: 11789681. DOI: 10.1093/bib/bbaf040.


Integration of 168,000 samples reveals global patterns of the human gut microbiome.

Abdill R, Graham S, Rubinetti V, Ahmadian M, Hicks P, Chetty A Cell. 2025; 188(4):1100-1118.e17.

PMID: 39848248 PMC: 11848717. DOI: 10.1016/j.cell.2024.12.017.


One Step Ahead in Realizing Pharmacogenetics in Low- and Middle-Income Countries: What Should We Do?.

Ausi Y, Barliana M, Postma M, Suwantika A J Multidiscip Healthc. 2024; 17:4863-4874.

PMID: 39464786 PMC: 11512769. DOI: 10.2147/JMDH.S458564.


Health Data Sciences and Cardiovascular Disease in Africa: Needs and the Way Forward.

Inam M, Sheikh S, Khoja A, Abubakar A, Shah R, Samad Z Curr Atheroscler Rep. 2024; 26(11):659-671.

PMID: 39240493 DOI: 10.1007/s11883-024-01235-1.


References
1.
Harris P, Taylor R, Thielke R, Payne J, Gonzalez N, Conde J . Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2008; 42(2):377-81. PMC: 2700030. DOI: 10.1016/j.jbi.2008.08.010. View

2.
Mulder N, Adebiyi E, Alami R, BenKahla A, Brandful J, Doumbia S . H3ABioNet, a sustainable pan-African bioinformatics network for human heredity and health in Africa. Genome Res. 2015; 26(2):271-7. PMC: 4728379. DOI: 10.1101/gr.196295.115. View

3.
Berman H, Westbrook J, Feng Z, Gilliland G, Bhat T, Weissig H . The Protein Data Bank. Nucleic Acids Res. 1999; 28(1):235-42. PMC: 102472. DOI: 10.1093/nar/28.1.235. View

4.
Shihab H, Gough J, Cooper D, Stenson P, Barker G, Edwards K . Predicting the functional, molecular, and phenotypic consequences of amino acid substitutions using hidden Markov models. Hum Mutat. 2012; 34(1):57-65. PMC: 3558800. DOI: 10.1002/humu.22225. View

5.
Chimusa E, Daya M, Moller M, Ramesar R, Henn B, van Helden P . Determining ancestry proportions in complex admixture scenarios in South Africa using a novel proxy ancestry selection method. PLoS One. 2013; 8(9):e73971. PMC: 3774743. DOI: 10.1371/journal.pone.0073971. View