BiobankConnect: software to rapidly connect data elements for pooled analysis across biobanks using ontological and lexical indexing
| Autor: | Martijn Dijkstra, Chao Pang, Joël Kuiper, K. Joeri van der Velde, Morris A. Swertz, Dennis Hendriksen, Hans L. Hillege |
|---|---|
| Přispěvatelé: | Life Course Epidemiology (LCE), Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI) |
| Rok vydání: | 2014 |
| Předmět: |
Matching (statistics)
Abstracting and Indexing Computer science Datasets as Topic Health Informatics Research and Applications computer.software_genre Set (abstract data type) User-Computer Interface 03 medical and health sciences 0302 clinical medicine Software SEARCH Humans 030212 general & internal medicine Biobank 030304 developmental biology 0303 health sciences Information retrieval Data collection GENE ONTOLOGY business.industry DATASHAPER APPROACH Rank (computer programming) Search engine indexing Computational Biology Systems Integration Biological Ontologies Harmonization Data integration User interface business INTEGRATION computer |
| Zdroj: | Journal of the American Medical Informatics Association : JAMIA Journal of the American Medical Informatics Association, 22(1), 65-75. B M J PUBLISHING GROUP |
| ISSN: | 1527-974X 1067-5027 |
| Popis: | Objective Pooling data across biobanks is necessary to increase statistical power, reveal more subtle associations, and synergize the value of data sources. However, searching for desired data elements among the thousands of available elements and harmonizing differences in terminology, data collection, and structure, is arduous and time consuming. Materials and methods To speed up biobank data pooling we developed BiobankConnect, a system to semi-automatically match desired data elements to available elements by: (1) annotating the desired elements with ontology terms using BioPortal; (2) automatically expanding the query for these elements with synonyms and subclass information using OntoCAT; (3) automatically searching available elements for these expanded terms using Lucene lexical matching; and (4) shortlisting relevant matches sorted by matching score. Results We evaluated BiobankConnect using human curated matches from EU-BioSHaRE, searching for 32 desired data elements in 7461 available elements from six biobanks. We found 0.75 precision at rank 1 and 0.74 recall at rank 10 compared to a manually curated set of relevant matches. In addition, best matches chosen by BioSHaRE experts ranked first in 63.0% and in the top 10 in 98.4% of cases, indicating that our system has the potential to significantly reduce manual matching work. Conclusions BiobankConnect provides an easy user interface to significantly speed up the biobank harmonization process. It may also prove useful for other forms of biomedical data integration. All the software can be downloaded as a MOLGENIS open source app from http://www.github.com/molgenis, with a demo available at http://www.biobankconnect.org. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|