Batch normalization followed by merging is powerful for phenotype prediction integrating multiple heterogeneous studies.

In our simulation studies, we observed a decreasing trend in prediction accuracy among all statistical methods we investigated when the population heterogeneity became large, the batch effects increased on training data, as well as the differences of disease models between training and test data enlarged.

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