+Breast cancer research benefits from a substantial collection of gene expression datasets that are commonly integrated to increase analytical power. Gene expression batch effects arising between experimental batches, where signal differences confound true biological variation, must be addressed when integrating datasets and several approaches exist to address these technical differences. In this work we demonstrate that popular batch correction techniques can significantly distort key biomarker expression signals. Through the implementation of ComBat batch correction and evaluation of integrated expression values, we profile the extent of these distortions and consider an additional mitigatory batch correction step.
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