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Data Stream Processing > Processing Modules > General manipulation Modules


The CalcFeatureSignificance processing module is designed to sit in the middle of a processing stream and transform the multiple Experiment / Expression data of a Feature into the single significance/score for that Feature.


  • <expression_mode> : defines how expression between different Experiments are combined together when calculating the Feature significance. Possible values are:
    • sum : sum the expression between different Experiments into the significance.
    • min : calculate the minimum expression value among different Experiments
    • max : calculate the maximum expression value among different Experiments
    • count : count the number of different Experiments of the Feature.
    • mean : calculate the average expression value among the different Experiments of the feature


This script combines FeatureEmitter / TemplateCluster strandless, expression histogram binning with a CalcFeatureSignificance. This can then be visualized in a hybrid track using a color spectrum.

	<spstream module="CalcFeatureSignificance">
	<spstream module="TemplateCluster">
			<spstream module="FeatureEmitter">