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CITATION.cff
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# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: ezomero
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Erick
orcid: 'https://orcid.org/0000-0002-7545-3675'
family-names: Martins Ratamero
affiliation: The Jackson Laboratory
- given-names: Kiya
family-names: Govek
affiliation: The Jackson Laboratory
orcid: 'https://orcid.org/0000-0002-2105-0715'
- given-names: Julio
family-names: Mateos-Langerak
affiliation: 'University of Montpellier, CNRS, INSERM'
orcid: 'https://orcid.org/0000-0003-1579-0773'
- given-names: Fernando
family-names: Cervantes Sanchez
affiliation: The Jackson Laboratory
orcid: 'https://orcid.org/0000-0003-0652-2750'
- given-names: David
family-names: Mellert
affiliation: The Jackson Laboratory
orcid: 'https://orcid.org/0000-0001-6606-0274'
repository-code: 'https://github.com/TheJacksonLaboratory/ezomero'
abstract: >-
Many research laboratories need to manage, process, and
analyze the increasingly large volumes and complexity of
data being produced by state-of-the-art bioimaging
platforms. OMERO is a popular open-source client-server
application that provides a unified interface for managing
and working with bioimages and their associated
measurements and metadata. Integrating OMERO into analysis
pipelines, such as those developed around the scientific
Python ecosystem, will thus be a common pattern across the
field of bioimaging. While OMERO has a powerful Python
API, it provides minimal abstraction from the underlying
OMERO object model and associated methods, which represent
more complexity than most users are interested in for the
context of an analysis script. We introduce ezomero, which
was designed to provide a convenience layer on top of
existing OMERO APIs and return data types that are either
Python primitive or commonly used in scientific Python.
Ezomero has minimal dependencies in addition to the OMERO
Python library itself and is installable directly from
PyPI. Here, we provide an overview of ezomero as well as
several vignettes to illustrate how it can be used to
accelerate discovery.
license: GPL-2.0
preferred-citation:
type: article
authors:
- given-names: Erick
orcid: 'https://orcid.org/0000-0002-7545-3675'
family-names: Martins Ratamero
affiliation: The Jackson Laboratory
- given-names: Kiya
family-names: Govek
affiliation: The Jackson Laboratory
orcid: 'https://orcid.org/0000-0002-2105-0715'
- given-names: Julio
family-names: Mateos-Langerak
affiliation: 'University of Montpellier, CNRS, INSERM'
orcid: 'https://orcid.org/0000-0003-1579-0773'
- given-names: Fernando
family-names: Cervantes Sanchez
affiliation: The Jackson Laboratory
orcid: 'https://orcid.org/0000-0003-0652-2750'
- given-names: David
family-names: Mellert
affiliation: The Jackson Laboratory
orcid: 'https://orcid.org/0000-0001-6606-0274'
title: "Easing OMERO adoption with ezomero"
doi: 10.1101/2023.06.29.546930