How DataCore Analytics Keeps Data Confidential
12 May 2026
DataCore Analytics is a bioinformatics, biostatistics and data science consultancy registered in Kenya and operating remotely across the continent.
We provide analysis, consultation, training and remote support to universities, research institutions, national reference laboratories, public health institutes, clinical trial units, biotechnology companies and non-governmental organisations. Our consultants work across genomics, transcriptomics, epigenomics, microbiome research, pathogen surveillance, epidemiology, clinical trials and machine learning.
We are an analysis-only organisation. We do not operate a wet laboratory and we do not handle physical samples. Data reaches us as sequence reads, matrices, variant files or study datasets, and leaves as interpreted results, publication-ready figures and reproducible code. That independence means our advice on study design carries no incentive to sell you sequencing you do not need, and we work equally well with data from any platform or provider.
Sequencing capacity across Africa expanded sharply during the COVID-19 response. Platforms were installed in national reference laboratories, universities and research institutes on a scale the continent had not seen before. Analysis capacity did not expand at the same rate.
The result is a structural bottleneck. Institutions generate genomic, epidemiological and clinical data faster than they can interpret it, and a large share of African research data is still analysed outside the continent — at high cost, on long turnaround, and with the analytical expertise accumulating somewhere else.
DataCore Analytics exists to close that gap, and to make sure the skills stay where the data is generated.
African populations carry more genetic diversity than the rest of the world combined, and are the most under-represented in the reference panels, annotation databases and training datasets that standard pipelines depend on. A pipeline tuned on European cohorts systematically misclassifies variants in African samples. A clinical prediction model trained on North American data frequently fails when deployed on an African population.
These are not abstract concerns. They change which variants get called, which associations reach significance and which models are safe to use. Analysts who work with African data every day build that awareness into the work by default.
The commitments below are written into every project agreement.
We do not sell sequencing. We work with data from any provider or instrument, and our study design advice has no commercial bias attached to it.
One consultant owns your project from scoping to handover, with a second reviewing. You are not routed through a ticket queue.
You approve a written analysis plan — methods, software, deliverables, timeline and fixed quote — before analysis begins.
Every deliverable ships with code, pinned software versions, reference genome versions and documentation. Your team can rerun it without us.
Access is restricted and logged, storage is encrypted, and we never reuse client data for other projects or model training without written permission.
Every partnership includes training for your own staff and students. We would rather teach your team the analysis than sell it to them twice.
Our services are used by research and public health organisations across the continent, from single-investigator projects through to national surveillance programmes.
DataCore Analytics is registered in Kenya and operates as a distributed organisation, with consultants working remotely from several African countries. Contracting, invoicing and data agreements are handled centrally.
No data is accepted without a written agreement covering scope, storage location, retention period, access, authorship and intellectual property. Where a project involves human subjects we ask to see the relevant ethical approval, and any applicable material or data transfer agreement, before work begins. Full detail is set out in our privacy and data handling policy.
We report what the data supports and no more. If an analysis is underpowered, confounded or compromised by data quality, we say so in the report rather than presenting a result that will not survive peer review. Analyses that were run and did not work are documented alongside those that did.
Our services are provided for research purposes. They are not intended for clinical diagnosis, treatment decisions or individual health assessment.
Bioinformatics, biostatistics and data science support for research teams across Africa.
12 May 2026
28 April 2026