Box-and-whisker plot summarizes marker expression statistics (median, IQR, 5th-95th percentile range) per population.
In order to see the Box plot then you should click on the 'Box plot' item in the 'Analysis' menu.
Then you should select populations and markers for the Box plot.
Then you will see the Box plot frame in the 'Analysis' tab. Each box colored by corresponding population color (black border for population with white color). You are able to change set of populations/markers by clicking on the corresponding buttons. Also you can click on the 'Export' button to export box plot as PNG.
Toggle markers normalization You can toggle markers normalization by clicking on the corresponding switch button. When normalization is enabled, all values will be normalized from 0 to 1.
Spatial analysis
Spatial analysis menu item If you want to perform Spatial analysis then you should click on corresponding item in the 'Analysis' menu. Clicking on it will display the following:
Specify the minimum and maximum distance in microns. Cells within this distance will be quantified as interacting. Minimum distance may not be smaller than 1 pixel (3 microns for this camera).
In the "Spatial Analysis" table for each existing population you can see number of interactions with another populations. You can recompute this table by clicking on the 'Compute' button. All table cells are colored by white-red color scheme where red means greater amount of interactions.
You can change 'Interaction count' option to 'LogsOdd ratio' option and click on the 'Compute' button. This number estimates relative likelihood of two cell types to engage in spatial interaction, relative to random chance (see this paper for detailed explanation of the Log Odds ratio). Then you will see table with blue-white-red color scheme where blue means negative log-odds ratio (interactions less frequent than expected by change), red means greater ratio (cells are interacting more frequently than expected by chance).
You can export this table by clicking on the 'Export' button. Then you will be able to choose destination of exported CSV file.
Graphically represent Spatial Interactions
Select the region of analysis.
Specify the minimum and maximum distance in microns. Cells within this distance will be quantified as interacting. Minimum distance may not be smaller than 1 pixel (3 microns for this camera).
Within the Spatial Analysis table click Circos, shown above outlined in red.
Optional Ribbon scaling
Scale arcs question dialog Choose 'Yes' for the Circos plot where population arcs have a different length (scaled by interactions count). Choose 'No' for the Circos plot where populations arcs have the same length.
Comparison of scaled and not scaled Circos plot The annotated Circos plot above graphically demonstrates spatial interactions. Both biomarker expression and population interaction are subject to color scaling according to the users’ preference. Biomarker color scaling
Scale population biomarker heatmap by all cells in dataset or by populations shown in Circos plot using your chosen color scheme. Population interaction color scaling and Opacity
Assign color scheme to population interaction ribbons Specify population interaction ribbon opacity Specify population interaction metric
Uncheck LogsOdd ratio to display the number of spatial interactions between populations Export Circos plot
Density heatmap
Density heatmap (all cells) menu item If you want to calculate Density heatmap for all cells then you should click on the corresponding item in the 'Analysis' menu.
The user needs to specify Gaussian blur parameters. Higher values of these parameters will give a higher blur effect on the resulting image.
Then Density heatmap activity will appear in the Background activities panel and the Density heatmap layer will appear on the region image.
Density heatmap for all cells Density heatmap for populations Users can choose to calculate the Density heatmaps for selected populations. In the "Populations" table, select populations by right-clicking and choosing the 'Density heatmap' option.
Density heatmap for populations result 
