MOLGENIS/connect: a system for semi-automatic integration of heterogeneous phenotype data with applications in biobanks

Chao Pang, David van Enckevort, Mark de Haan, Fleur Kelpin, Jonathan Jetten, Dennis Hendriksen, Tommy de Boer, Bart Charbon, Erwin Winder, K. Joeri van der Velde, Dany Doiron, Isabel Fortier (+2 others)
2016 Bioinformatics  
Motivation: While the size and number of biobanks, patient registries and other data collections are increasing, biomedical researchers still often need to pool data for statistical power, a task that requires time-intensive retrospective integration. Results: To address this challenge, we developed MOLGENIS/connect, a semi-automatic system to find, match and pool data from different sources. The system shortlists relevant source attributes from thousands of candidates using ontology-based
more » ... expansion to overcome variations in terminology. Then it generates algorithms that transform source attributes to a common target DataSchema. These include unit conversion, categorical value matching and complex conversion patterns (e.g. calculation of BMI). In comparison to human-experts, MOLGENIS/connect was able to auto-generate 27% of the algorithms perfectly, with an additional 46% needing only minor editing, representing a reduction in the human effort and expertise needed to pool data. Availability and Implementation: Source code, binaries and documentation are available as opensource under LGPLv3 from
doi:10.1093/bioinformatics/btw155 pmid:27153686 pmcid:PMC4937195 fatcat:6viasbcnrfh3haoih4lhocngxa