Metadata management for high content screening in OMERO

Simon Li; Sébastien Besson; Colin Blackburn; Mark Carroll; Richard K. Ferguson; Helen Flynn; Kenneth Gillen; Roger Leigh; Dominik Lindner; Melissa Linkert; William J. Moore; Balaji Ramalingam; Emil Rozbicki; Gabriella Rustici; Aleksandra Tarkowska; Petr Walczysko; Eleanor Williams; Chris Allan; Jean Marie Burel; Josh Moore; Jason R. Swedlow

doi:10.1016/j.ymeth.2015.10.006

Metadata management for high content screening in OMERO

Simon Li, Sébastien Besson, Colin Blackburn, Mark Carroll, Richard K. Ferguson, Helen Flynn, Kenneth Gillen, Roger Leigh, Dominik Lindner, Melissa Linkert, William J. Moore, Balaji Ramalingam, Emil Rozbicki, Gabriella Rustici, Aleksandra Tarkowska, Petr Walczysko, Eleanor Williams, Chris Allan, Jean Marie Burel, Josh MooreJason R. Swedlow

Gene Regulation and Expression

Research output: Contribution to journal › Article › peer-review

14 Citations (Scopus)

163 Downloads (Pure)

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	https://doi.org/10.1016/j.ymeth.2015.10.006
Publication status	Published - 1 Mar 2016

Keywords

Data management
HCS
Metadata
Screening

Access to Document

10.1016/j.ymeth.2015.10.006Licence: CC BY

Final Published Version
©2015 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Final published version, 510 KBLicence: CC BY

Link to publication in Scopus

Fingerprint Dive into the research topics of 'Metadata management for high content screening in OMERO'. Together they form a unique fingerprint.

3 Finished

Building a Next Generation Image Repository: Molecular Annotation and Cloud-based Data Processing and Analysis (Joint with EMBL-EBI and University of Cambridge)
Swedlow, J.
Biotechnology and Biological Sciences Research Council
1/01/15 → 30/06/16
Project: Research
Expanded Metadatas Support in the Open Microscopy Environments Bio-Formats and OMERO Data Applications
Swedlow, J.
Biotechnology and Biological Sciences Research Council
31/08/14 → 28/02/18
Project: Research
The Open Microscopy Environment: Image Informatics for Biological Sciences (Joint with Imperial College, Oxford University, Institut Pasteur, Carnegie-Mellon University, University of Wisconsin, Harvard Medical School & University of Edinburgh)
Swedlow, J.
Wellcome Trust
1/10/11 → 30/09/16
Project: Research

Swedlow, Jason
- Gene Regulation and Expression - Professor & Personal Chair of Quantitative Cell Biology
Person: Academic

Cite this

Li, S., Besson, S., Blackburn, C., Carroll, M., Ferguson, R. K., Flynn, H., Gillen, K., Leigh, R., Lindner, D., Linkert, M., Moore, W. J., Ramalingam, B., Rozbicki, E., Rustici, G., Tarkowska, A., Walczysko, P., Williams, E., Allan, C., Burel, J. M., ... Swedlow, J. R. (2016). Metadata management for high content screening in OMERO. Methods, 96, 27-32. https://doi.org/10.1016/j.ymeth.2015.10.006

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. / Metadata management for high content screening in OMERO. In: Methods. 2016 ; Vol. 96. pp. 27-32.

@article{3e5fd9f4153f4dd7b431c7316fa9a777,

title = "Metadata management for high content screening in OMERO",

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.",

keywords = "Data management, HCS, Metadata, Screening",

author = "Simon Li and S{\'e}bastien Besson and Colin Blackburn and Mark Carroll and Ferguson, {Richard K.} and Helen Flynn and Kenneth Gillen and Roger Leigh and Dominik Lindner and Melissa Linkert and Moore, {William J.} and Balaji Ramalingam and Emil Rozbicki and Gabriella Rustici and Aleksandra Tarkowska and Petr Walczysko and Eleanor Williams and Chris Allan and Burel, {Jean Marie} and Josh Moore and Swedlow, {Jason R.}",

note = "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).",

year = "2016",

month = mar,

day = "1",

doi = "10.1016/j.ymeth.2015.10.006",

language = "English",

volume = "96",

pages = "27--32",

journal = "Methods (San Diego, Calif.)",

issn = "1046-2023",

publisher = "Elsevier",

}

Li, S , Besson, S, Blackburn, C, Carroll, M, Ferguson, RK, Flynn, H, Gillen, K, Leigh, R, Lindner, D, Linkert, M, Moore, WJ, Ramalingam, B, Rozbicki, E, Rustici, G, Tarkowska, A, Walczysko, P, Williams, E, Allan, C, Burel, JM, Moore, J & Swedlow, JR 2016, 'Metadata management for high content screening in OMERO', Methods, vol. 96, pp. 27-32. https://doi.org/10.1016/j.ymeth.2015.10.006

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 › peer-review

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 -

Metadata management for high content screening in OMERO

Abstract

Keywords

Access to Document

Building a Next Generation Image Repository: Molecular Annotation and Cloud-based Data Processing and Analysis (Joint with EMBL-EBI and University of Cambridge)

Expanded Metadatas Support in the Open Microscopy Environments Bio-Formats and OMERO Data Applications

The Open Microscopy Environment: Image Informatics for Biological Sciences (Joint with Imperial College, Oxford University, Institut Pasteur, Carnegie-Mellon University, University of Wisconsin, Harvard Medical School & University of Edinburgh)

Swedlow, Jason

Cite this