Many good comments, thanks for sharing everyone! We run Omero on Centos7 in AWS using the dual server and webserver configuration. I struggled to install it, but it was only mildly difficult for the capable sysadmin person I have access to. It’s been super stable and big timesaver. Our images are often a few Gb in size and viewing the images is fast and powerful. I wish I had tried Omero sooner. The Figure tool alone is worth the price of admission. Promote whoever designed that immediately.
Arborvitae’s question about study metadata was a big one for us. For plate based work there are built-in annotation tools, but bulk uploading annotations for a “Dataset” thru the webclient is not currently possible. It is easy to annotate manually using the UI, but that is not sustainable if there are many images and/or many annotations. I tried using tables, but it turns out that the Parade tool for searching annotations can’t handle a mix of numbers and strings (numbers only, again future versions may include this function) so I switched to key-value pairs and figured out how to use the command line interface (CLI). The CLI is bundled with the server and is very useful.
This is an example of how to make that work.
Omero and the metadata module. The metadata module is not the same as the Populate Metadata function and which can import metadata for a plate or a screen (many plates), but not a Dataset at this time.
Images that have been uploaded to Omero. Many ways to do this; we use the InSight client.
a .csv with the annotations. If using excel save as a “Comma Separated Values (.csv)”. Other formats might not work and always use a text editor that plays nice with the unix kids in the sandbox. Image Name and Dataset Name are required. Use the image name given by omero and the dataset created during image upload. This is a screenshot of what that might look like in excel:
- a .yml file to tell the metadata module what to do with the annotations. Shown is a screenshot in TextEdit that I adapted from a dataset in the IDR (website mentioned earlier worth investigating). Add as many columns as necessary, but make sure the name matches the column name (exactly) in the .csv file. Everything after the last “include: true” is required, but not doing anything in this example:
Both the .csv and .yml files need to be in a place that the CLI can access. It’s easy to upload files through the webclient or InSight tool. I struggled to link them to CLI commands. I use sftp to move the files to the omero server from my laptop and I make sure they are owned by the omero user.
Then, finally, these commands can be run on the server using the CLI (as the omero user with admin privileges):
[omero@ip home]$ ~/OMERO.server/bin/omero metadata populate Dataset:382 --cfg omero_test-bulkmap-config.yml --file omero_test_annotations.csv
[omero@ip home]$ ~/OMERO.server/bin/omero metadata populate --context bulkmap --cfg omero_test-bulkmap-config.yml Dataset:382
and then, if all goes well, the images are annotated with the key value pairs from the .csv:
now the annotations can be used to search for images with the Parade tool (another module that needs to be installed). Here the image matching two key value filters is shown in the middle panel:
if the annotations need to be updated this command will delete them and one can start over with the above commands:
~/OMERO.server/bin/omero delete Dataset/MapAnnotation:382