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reComBat: Batch effect removal in large-scale, multi-source omics data integration
With the steadily increasing abundance of omics data produced all over the world, sometimes decades apart and 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 and coincide of both batches and desired, biological variation resulting in design matrix singularity. This problem currently cannot bedoi:10.5451/unibas-ep87154 fatcat:5axqlxhp6jfbve5oynfpvzhq3e