The Remove batch effect tool functions much like ANOVA in reverse, calculating the variation attributed to the factor(s) being removed then adjusting the original values to remove the variation. 

By including batch in the differential analysis model, the variability due to the batch effect is accounted for when calculating p-values. In this sense, batch effects are best handled as part of the differential analysis model. However, clustering data or visualizing biological effects can be very difficult if batch effects are present in the original data. We can modify the original values to remove the batch effect using the Remove batch effect tool. 

What is Remove batch effect?

The Remove batch effect tool functions much like ANOVA in reverse, calculating the variation attributed to the factor(s) being removed then adjusting the original values to remove the variation. 

Running Remove batch effect

We recommend normalizing your data prior to removing batch effects, but the task will run on any counts data node. 

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Remove batch effect advanced options

The advanced options for Remove batch effect are shared by ANOVA. 

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