Glencoe Software presents updated interoperability between OMERO and open-source image analysis tools, such as CellProfiler.
Both OMERO and OMERO Plus provide a scalable and flexible platform for management of microscopy data. Backed by the Bio-Formats library, OMERO can natively store and retrieve image formats arising from a wide variety of microscopy hardware. Objects on OMERO can also be associated with relevant metadata and tabular analysis results in the form of OMERO.tables. Together, this means that large and complex image datasets and their associated analysis results can be both stored and retrieved remotely. To further increase the utility of this system, users requested closer integration with existing analysis and data science tools for processing stored data.
To provide a more convenient method for working with OMERO.tables from Python environments, Glencoe Software have released the open source omero2pandas package. This package allows users to load and save OMERO.table data as pandas dataframes, with additional integration aimed towards Jupyter notebooks. This provides access to the full suite of Python data science packages when working with OMERO data, without the need for the user to have extensive experience with the OMERO Python API.
To further improve connectivity with other data analysis tools, we have also rebuilt and enhanced OMERO support within the popular CellProfiler analysis software. The new plugin, targeted at the forthcoming CellProfiler 5 release, provides a more feature-rich experience for loading data into pipelines. We have also developed dedicated export modules allowing users to directly upload results back onto OMERO. Together this new integration provides the opportunity to run analysis pipelines and return results on remotely stored data. These tools will provide imaging scientists with user-friendly and effective tools for working with data managed on OMERO.