Image data resource – introduction

Trainer: Jason Swedlow

Overview: IDR links data from several imaging modalities, including high-content screening, multi-dimensional microscopy and digital pathology, with public genetic or chemical databases and cell and tissue phenotypes expressed using controlled ontologies. Using this integration, IDR facilitates the analysis of gene networks and reveals functional interactions that are inaccessible to individual studies. To enable reanalysis, we also established a computational resource based on Jupyter notebooks that allows remote access to the entire IDR. IDR is also an open-source platform for publishing imaging data. Thus IDR provides an online resource and a software infrastructure that promotes and extends publication and reanalysis of scientific image data. (Segment from the abstract at Nature Methods: https://doi.org/10.1038/nmeth.4326)

Learning outcomes:

After this section you should be able to:

Identify the resources available at the IDR and their relevance in bioimage analysis.

Materials:

Presentation (from the 2022 course)

Find more information about submissions to IDR: https://idr.openmicroscopy.org/about/submission.html
Examples of benchmarking of different binary structures for bioimaging data: OME-NGFF: a next-generation file format for expanding bioimaging data-access strategies

Other resources:

Microscopy data analysis: machine learning and the BioImage Archive

Image data resource – introduction