The Plate Editor can annotate FCS files from plate-based assays.
High-throughput plate-based assays are increasingly common in flow cytometry. Working with collections of 96, 384, or 1536 wells at a time adds additional dimensionality to the biological questions that can be asked, the amount of data presents management and annotation challenges. FlowJo’s structured approach to groups supports this throughput and the plate editor facilitates data annotation and further automated analysis using a template.
The Plate Editor:
- Facilitates metadata labeling with keyword-value pairs before data acquisition
- Allows a plate definition and annotation to be linked to a set of files though the WELLID keyword
- Improves analysis of the linked data-metadata through templates, i.e., pre-defined gating, statistics, and reports.
To access the Plate Editor, you will need to add the Experiment band to your ribbon.
Click on the ribbon icon in the top right corner of your workspace, select the visualizations band, and drag and drop this band onto your Ribbon.
The Plate Editor is the third action:
Figure 1: The Experiment Band
The window shown in Figure 2 is used to annotate plate-based data by individual well or groups of wells.
The center panel contains the individual wells, laid out to look like a plate and labeled with the well ID, that can be selected for annotation by dragging keywords from the list at the right or dragging a set of keywords from a staging well. Individual or multiple keywords (via the staging well) can be dragged to a header to add that annotation to the corresponding row or column.
The panel to the right is where annotation from the files in the workspace is visible, keywords and values can be added, and these keyword-value pairs dragged and dropped into the plate.
Figure 2: The Plate Editor
In this manner, you can annotate a plate before a run and direct the annotation, organization, and eventually analysis of data from your plate-based assays.
For more information on how to add annotation to a plate or visualize plate-based data and more, please see: