PyOmeroUpload: A Python toolkit for uploading images and metadata to OMERO [version 1; peer review: 2 approved]

Clicks: 33
ID: 276996
2020
Tools and software that automate repetitive tasks, such as metadata extraction and deposition to data repositories, are essential for researchers to share Open Data, routinely. For research that generates microscopy image data, OMERO is an ideal platform for storage, annotation and publication according to open research principles. We present PyOmeroUpload, a Python toolkit for automatically extracting metadata from experiment logs and text files, processing images and uploading these payloads to OMERO servers to create fully annotated, multidimensional datasets. The toolkit comes packaged in portable, platform-independent Docker images that enable users to deploy and run the utilities easily, regardless of Operating System constraints. A selection of use cases is provided, illustrating the primary capabilities and flexibility offered with the toolkit, along with a discussion of limitations and potential future extensions. PyOmeroUpload is available from: https://github.com/SynthSys/pyOmeroUpload.
Reference Key
hay2020pyomerouploadwellcome Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Hay, Johnny;Troup, Eilidh;Clark, Ivan;Pietsch, Julian;Zieliński, Tomasz;Millar, Andrew;
Journal Wellcome open research
Year 2020
DOI DOI not found
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.