Create OMERO.tables and analyze metadata using OMERO.parade

Updated 1,007 Days AgoPublic

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Create OMERO.tables from a csv file

Description:

OMERO.tables unifies the storage of columnar data from various sources, such as automated analysis results or script-based processing, and makes them dynamically available within OMERO.

Ressources:

Dataset: Copy the folder called NEDD from:

WIN: \\svfas6.epfl.ch\biop\public\0-BIOP_Data\0-Install\OMERO\demo dataset analysis v2
MAC: smb://svfas6.epfl.ch/biop/public/0-BIOP_Data/0-Install/OMERO/demo dataset analysis v2

CSV file: Copy the file four-NEDD-images.csv from:

WIN: \\svfas6.epfl.ch\biop\public\0-BIOP_Data\0-Install\OMERO\demo extra files
MAC: smb://svfas6.epfl.ch/biop/public/0-BIOP_Data/0-Install/OMERO/demo extra files

Step-by-Step:

1. Upload the folder called NEDD to OMERO as a Dataset and in OMERO, name this dataset NEDD.
2. In OMERO.web, attach the four-NEDD-images.csv file to your NEDD Dataset using the + button under the Attachments harmonica from the right panel.
   
3. Select the NEDD dataset and click on the button from the top menu bar of omero web .
4. Go to import_scripts → Populate Metadata.... Run the script
5. Select the NEDD dataset from the left-hand pane and observe in the right hand pane under “Attachments” that there is a new file called bulk_annotations attached to your NEDD dataset. This is your newly created OMERO.table, that can be opened from the web by hitting the button. It contains in each line a dynamic link to the corresponding image in OMERO.web
   
   Back to OMERO.web's main page, clic on one of the images from the NEDD dataset without opening it with the iviewer. Look at the Tables harmonica from the right-hand pane. Observe that all the statistics from the OMERO.table that apply to the selected image are gathered here.
   

2. Create OMERO.tables from FIJI's scripting editor

Follow the Analyze OMERO data in batch using the Scripting editor in Fiji step-by-step tutorial from this page

3. Analyze metadata using OMERO.parade

Description:

OMERO.parade is a metadata-mining plugin for OMERO.web. It enables access to the metadata of images in OMERO for plotting, display and filtering of images. Supported metadata includes number of ROIs, Key-Value pairs, and data stored in OMERO.tables or in .csv files. OMERO.tables are not required to use the OMERO.parade data mining tool.

Ressources:

Data: Copy and import to OMERO the folder called EdU RFP from:

WIN: \\svfas6.epfl.ch\biop\public\0-BIOP_Data\0-Install\OMERO\demo dataset analysis v2
MAC: smb://svfas6.epfl.ch/biop/public/0-BIOP_Data/0-Install/OMERO/demo dataset analysis v2

Scripts:
Groovy script for running a macro in batch (on a whole OMERO dataset) using Fiji:

Step-by-Step:

Filter images based on analysis data (from a .csv file or an OMERO.table)

1. Select the Edu RFP dataset, and drag and drop it in the hierarchy so that it is not included in a project.
2. Choose the Parade option in the centre panel dropdown menu from OMERO.web's main page.
3. In the Add filter selection box, select my_csv_filename.csv
4. Select data from the result table using the drop-down menu (i.e PosCellCount3) and drag the slider to filter the Images. Add as many filters as you want to fine-tune the research.

Create a dynamic scatter plot of your dataset based on analysis data (from a .csv file or an OMERO.table)

1. Remove all filters by hitting X and change the OMERO.parade layout to Table (middle button located under the Parade dropdown menu):
   
2. In the selection box Add table data…, select : Table_%Area, ROI_count, Table_PosCellCount2, Table_PosCellCount3. Note: you could also use the same data from the csv file.
3. Note that it is currently not possible to remove a column.
4. Click on the name of a column to sort it
5. Check the checkbox in each column to show the Heatmap. Note the corresponding pattern in the Heatmap.
6. Switch to the Plot layout (third button located under the Parade dropdown menu):
   
7. It takes the first 2 columns of pre-selected table data (from step 2.) to create a scatter plot. Each point corresponds to an image from the dataset.
8. Filters can be added to plot only the relevant results. (See part Filter images based on analysis data (from a .csv file or an OMERO.table))
9. Try to dynamically change the axes: select Table_PosCellCount2 and Table_PosCellCount3
10. Click on a point to select an outlier, or draw a rectangle by dragging your mouse to select several outliers at the same time
11. Draw a rectangle over the points at (0.0) : all the double-negative (EdU-, RFP-) images are selected in the left-hande pane
    
12. Selected images can be annotated using the options from the right-hand pane, viewed with the iviewer, or even opened in OMERO.figures!
13. Closing a Dataset in the left-hand tree removes the values from the plot.