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In the dialog, select attribute. The available attributes are categorical attributes can be seen on the data node which includes project level attributes and data node local annotation--, e.g. graph-based cluster result (Figure 1). If the task is run on graph-based clustering output data node, the calculation is using upstream data node which contains feature count feature counts – typically the input data node of PCA.

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Click on the Configure of Advanced option options to change the criteria on output features (Figure 2).

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By default, the result outputs the top 10 features that are up-regulated at least 1.5 fold change (in linear scale) for each subgroup comparing to others (ranked by the ascending p-values within each category). The result is displayed in a table with each column is a subgroup name, each row is a feature. An example is shown in Figure 3. 

Furthermore, the Download link (lower right corner of the table report; Figure 3) downloads a .txt file to the local computer (default file name: Biomarkers.txt), which contains the full report: all the genes with fold change > 1.5, with corresponding fold change and p-values. If a subgroup has fewer biomarkers than the others, the "extra" table fields for that subgroup will be left blank.

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