reComBat: batch-effect removal in large-scale multi-source gene-expression data integration

Michael F Adamer, Sarah Brueningk, Alejandro Tejada-Arranz, Fabienne Estermann, Marek Basler, Karsten Borgwardt

Abstract: With the steadily increasing abundance of omics data produced all over the world under vastly different experimental conditions residing in public databases, a crucial step in many data-driven bioinformatics applications is that of data integration. The challenge of batch-effect removal for entire databases lies in the large number of batches and biological variation, which can result in design matrix singularity. This problem can currently not be solved satisfactorily by any common batch-correction algorithm.