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In the dialog, select attribute. The available attributes are categorical attribute attributes can be seen on the data node which includes project level attribute 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–typically feature count – typically the input data node of PCA.
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Click on the Configure of Advanced option to change the criteria of on output features (Figure 2).
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By default, the result outputs features that are up-regulated at least 1.5 5 fold change (in linear scale) fold change for each subgroup comparing to others. The result is displayed in a table with each column is a subgroup name, each row is a feature.
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