Easing OMERO adoption with 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.