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The term batch effects, often used in the biological community, describes a situation where subsets (batches) of the measurements significantly differ in distribution, due to irrelevant instrument-related factors (Leek et al., 2010). Batch effects introduce systematic error, which may cause statistical analysis to produce spurious results and/or obfuscate the signal of interest. Typically, the systematic effect of varying instrument conditions on the measurements depends on many unknown factors, whose impact on the difference between the observed and underlying true signal cannot be modeled
(Leek et al., 2010) Tackling the widespread and critical impact of batch effects in high-throughput data. Nat Rev Genet.
(Shaham et al., 2017) Removal of batch effects using distribution-matching residual networks. Bioinformatics.