bapred: Batch Effect Removal (in Phenotype Prediction using Gene Data)

Various tools dealing with batch effects, in particular enabling the removal of discrepancies between training and test sets in prediction scenarios. The following batch effect removal methods are implemented: FAbatch, ComBat, (f)SVA, mean-centering, standardization, Ratio-A and Ratio-G. For each of these we provide an additional function which enables a posteriori ('addon') batch effect removal in independent batches ('test data'). Here, the (already batch effect adjusted) training data is not altered. For evaluating the success of batch effect adjustment several metrics are provided. Moreover, the package implements a plot for the visualization of batch effects using principal component analysis. The main functions of the package are ba() and baaddon() which enable batch effect removal and addon batch effect removal, respectively, with one of the seven methods mentioned above. Another important function is bametric() which is a wrapper function for all implemented methods for evaluating the success of batch effect removal.

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