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Abstract
High content screening (HCS) experiments create a classic data management challenge-multiple, large sets of heterogeneous structured and unstructured data, that must be integrated and linked to produce a set of "final" results. These different data include images, reagents, protocols, analytic output, and phenotypes, all of which must be stored, linked and made accessible for users, scientists, collaborators and where appropriate the wider community. The OME Consortium has built several open source tools for managing, linking and sharing these different types of data. The OME Data Model is a metadata specification that supports the image data and metadata recorded in HCS experiments. Bio-Formats is a Java library that reads recorded image data and metadata and includes support for several HCS screening systems. OMERO is an enterprise data management application that integrates image data, experimental and analytic metadata and makes them accessible for visualization, mining, sharing and downstream analysis. We discuss how Bio-Formats and OMERO handle these different data types, and how they can be used to integrate, link and share HCS experiments in facilities and public data repositories. OME specifications and software are open source and are available at. https://www.openmicroscopy.org.
Original language | English |
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Pages (from-to) | 27-32 |
Number of pages | 6 |
Journal | Methods |
Volume | 96 |
Early online date | 22 Oct 2015 |
DOIs | |
Publication status | Published - 1 Mar 2016 |
Keywords
- Data management
- HCS
- Metadata
- Screening
ASJC Scopus subject areas
- Molecular Biology
- Biochemistry, Genetics and Molecular Biology(all)
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Swedlow, Jason
- Molecular Cell and Developmental Biology - Professor of Quantitative Cell Biology, Program Director of Quantitative Cell Biology
Person: Secondment, Academic