Data analysis across databases

Conventional methods to physically pool individual participant data can raise ethical, legal and regulatory questions, and introduce data governance issues. These can become particularly complex when researchers are operating in a global context. The primary aim of BioSHaRE is to facilitate data analyses across multiple databases: our analytic solutions are tailored specifically to multiple cohort studies, and are designed in such a way as to minimize these issues while maintaining data security and increasing scientific power.

The tools for data analysis developed in BioSHaRE are designed for biobanks and cohort studies to accurately estimate sample size and power, and to allow for more flexible and secure data analysis between cohort studies.


Tool Description Keywords Website Demo
Data Analysis Across Databases
DataSHIELD Data Aggregation Through Anonymous Summarystatistics from Harmonised Individual levEL Databases. Data pooling, data analysis, federated analysis, sensitive data, governance, intellectual property
ESPRESSO Estimating Sample-size and Power in R by Exploring Simulated Study Outcomes Statistical power, sample size, association studies, measurement errors