One of our most powerful plugins is now native in FlowJo v10.9! Explore populations found with clustering tools through interactive plots displaying population frequencies, marker profiles, and clusters overlaid on low-dimension maps. Images can be copied to the clipboard or FlowJo layout editor.
Using Cluster Explorer
Cluster Explorer is used after performing clustering (ex: FlowSOM, Phenograph) and dimensionality reduction (ex: tSNE, UMAP) with other FlowJo plugins or tools. To launch the tool, select a population that has had clustering performed on it. Then select “Cluster Explorer” from the ribbon under “Populations” in the “Workspace” tab.
After selecting “Cluster Explorer” from the ribbon, a window will appear asking the user to select additional inputs. The window is divided into three sections. At the top, the user should select the clustering output(s) they want to view and compare. Multiple clustering outputs can be selected, but only one can be visualized at a time. The middle section allows the user to pick parameters to visualize. Usually it is most appropriate to choose the compensated parameters. The bottom section allows the user to choose any dimensionality reduction x and y parameters to display the clusters on. Multiple sets of dimensionality reduction parameters can be selected.
Once the parameters are selected, Cluster Explorer will generate a heatmap, profile graph, bar chart and the overlaid dimensionality reduction plots for the cluster populations. The control panel provides options for the various pieces of cluster explorer.
The bar chart shows the frequency (%) of each cluster in the population selected from the workspace. Under “Options”, uncheck “Normalize” to change the display to number of events per cluster. Double-click a single bar (cluster) to change the color of that cluster throughout the interface. Export values by selecting “Copy content” from the “Edit” tab, then pasting the comma-delimited values into a spreadsheet or text file.
The profile chart shows the relative intensity of each parameter for each cluster. Each line represents a cluster, with the color of the line matching the color legend displayed throughout the interface. There is an option under the “Clusters” tab at the top of the screen to remove outliers, which will remove cells from the plots whose signal fall outside of certain percentile thresholds. Here, users also have the ability to merge clusters and export them back into the workspace for further analysis. The “Options” tab contains choices for changing the appearance of the chart.
The heatmap shows the relative intensity of each parameter for a given cluster. Visualize additional populations in the heatmap by selecting “Add nodes as columns” under the “Options” tab, which displays the frequency of each added node within the cluster. Users can also choose from one of four color palettes for the heatmap display. Add or remove parameters to the heatmap using the “+” button on the far right of the plot. To export expression values, select “Copy content” from the “Edit” tab, then paste the comma-delimited values into a spreadsheet or text file.
If dimensionality reduction parameters are chosen, biaxial plots will also be displayed with clusters overlaid on those maps. Click on either axis to change the parameters being plotted. Other display changes can be made in the “Options” tab. Open new biaxial plots by clicking “2D plot” in the Control Panel.
All the plots are interactive and if a cluster is selected in one plot, that same cluster will be highlighted in the other plots. Double clicking on the white space of any plot will reset which clusters are selected. Screen capture any of the plots by selecting “Copy image” under the “Edit” tab.
Click-and-drag the mouse over points in the profile plot to form gates around clusters. The “Profile Gates” section of the control panel has options for Boolean logic to select points within the plot. Choose “And” to highlight only the clusters that are within all of the profile plot gates. Choose “Not” to highlight all the clusters not present on the profile plot gates. Select “Clear Gates” to remove any gates drawn on the profile plot and “Restore Gates” to return them to the display.
In the “Cluster Set” section of the control panel, the “Compare to” button will open a new window that allows comparison between different cluster sets. The comparison will try to match clusters that seem to contain similar populations between the two cluster sets. Select one of three similarity metrics to display in the matrix from the “Options tab” (number of mutual events, Jaccard Index, or F-measure). The Jaccard Similarity Measure, at the top of the window, scores the degree of “overlap” between the two cluster sets on a scale from 0 to 1, with higher values indicating more overlap. Export values by selecting “Copy content” from the “Edit” tab, then pasting the comma-delimited values into a spreadsheet or text file.
If you have any questions about Cluster Explorer, reach out to email@example.com.