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Sharing and reusing cell image data.

Assaf Zaritsky
Molecular biology of the cell | 2018

The rapid growth in content and complexity of cell image data creates an opportunity for synergy between experimental and computational scientists. Sharing microscopy data enables computational scientists to develop algorithms and tools for data analysis, integration, and mining. These tools can be applied by experimentalists to promote hypothesis-generation and discovery. We are now at the dawn of this revolution: infrastructure is being developed for data standardization, deposition, sharing, and analysis; some journals and funding agencies mandate data deposition; data journals publish high-content microscopy data sets; quantification becomes standard in scientific publications; new analytic tools are being developed and dispatched to the community; and huge data sets are being generated by individual labs and philanthropic initiatives. In this Perspective, I reflect on sharing and reusing cell image data and the opportunities that will come along with it.

Pubmed ID: 29851565

Research resources used in this publication

None found

Additional research tools detected in this publication

Antibodies used in this publication

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Associated grants

  • Agency: NIGMS NIH HHS, United States
    Id: P01 GM103723

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


JCB DataViewer (tool)

RRID:SCR_002633

A web-based, multi-dimensional image data-viewing application for original microscopy image datasets associated with articles published in The Journal of Cell Biology, a peer-reviewed journal published by The Rockefeller University Press. The JCB DataViewer can host multidimensional fluorescence microscopy images, 3D tomogram data, very large (gigapixel) images, and high content imaging screens. Images are presented in an interactive viewer, and the scores from high content screens are presented in interactive graphs with data points linked to the relevant images. The JCB DataViewer uses the Bio-Formats library to read over 120 different imaging file formats and convert them to the OME-TIFF image data standard. Image data are archived by the Journal and may be freely accessed by readers using the JCB DataViewer. Download of author-provided image data and associated metadata in OME-TIFF format is also possible with author permission, allowing for independent analysis of image data irrespective of acquisition or viewing software. Although the JCB DataViewer is designed to host and facilitate sharing and analysis of original microscopy image data, authors may also upload other types of original image data as supplements to their manuscripts, including histology and electron micrographs and digital scans of gels or blots.

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GigaDB (tool)

RRID:SCR_004002

Repository to host data and tools associated with articles in GigaScience; however, it also includes a subset of datasets that are not associated with GigaScience articles. GigaDB defines a dataset as a group of files (e.g., sequencing data, analyses, imaging files, software programs) that are related to and support an article or study. Through their association with DataCite, each dataset will be assigned a DOI that can be used as a standard citation for future use of these data in other articles by the authors and other researchers. Datasets in GigaDB all require a title that is specific to the dataset, an author list, and an abstract that provides information specific to the data included within the set. Detailed information about the data to be submitted is encouraged in ISA-Tab, a format used by the BioSharing and ISA Commons communities that they work with to maintain the highest data and metadata standards in their journal.

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