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 |
|---|---|
| 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 |
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Keywords
- Data management
- HCS
- Metadata
- Screening
Cite this
}
Metadata management for high content screening in OMERO. / Li, Simon; Besson, Sébastien; Blackburn, Colin; Carroll, Mark; Ferguson, Richard K.; Flynn, Helen; Gillen, Kenneth; Leigh, Roger; Lindner, Dominik; Linkert, Melissa; Moore, William J.; Ramalingam, Balaji; Rozbicki, Emil; Rustici, Gabriella; Tarkowska, Aleksandra; Walczysko, Petr; Williams, Eleanor; Allan, Chris; Burel, Jean Marie; Moore, Josh; Swedlow, Jason R. (Lead / Corresponding author).
In: Methods, Vol. 96, 01.03.2016, p. 27-32.Research output: Contribution to journal › Article
TY - JOUR
T1 - Metadata management for high content screening in OMERO
AU - Li, Simon
AU - Besson, Sébastien
AU - Blackburn, Colin
AU - Carroll, Mark
AU - Ferguson, Richard K.
AU - Flynn, Helen
AU - Gillen, Kenneth
AU - Leigh, Roger
AU - Lindner, Dominik
AU - Linkert, Melissa
AU - Moore, William J.
AU - Ramalingam, Balaji
AU - Rozbicki, Emil
AU - Rustici, Gabriella
AU - Tarkowska, Aleksandra
AU - Walczysko, Petr
AU - Williams, Eleanor
AU - Allan, Chris
AU - Burel, Jean Marie
AU - Moore, Josh
AU - Swedlow, Jason R.
N1 - This work was supported by a Wellcome Trust Strategic Award (095931/Z/11/Z) and two BBSRC BBR awards (BB/L024233/1 and BB/M018423/1).
PY - 2016/3/1
Y1 - 2016/3/1
N2 - 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.
AB - 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.
KW - Data management
KW - HCS
KW - Metadata
KW - Screening
UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-84958183670&origin=resultslist&sort=plf-f&src=s&st1=Metadata+management+for+high+content+screening+in+OMERO&st2=&sid=1600EAF16BEDB6C13A549DFFE1C48DAE.wsnAw8kcdt7IPYLO0V48gA%3a20&sot=b&sdt=b&sl=70&s=TITLE-ABS-KEY%28Metadata+management+for+high+content+screening+in+OMERO%29&relpos=0&citeCnt=1&searchTerm=
U2 - 10.1016/j.ymeth.2015.10.006
DO - 10.1016/j.ymeth.2015.10.006
M3 - Article
C2 - 26476368
VL - 96
SP - 27
EP - 32
JO - Methods (San Diego, Calif.)
JF - Methods (San Diego, Calif.)
SN - 1046-2023
ER -