Table 1.

Terminology.

Term	Definition
Batch effects	Systematic differences between the measurements due to technical factors, such as sample or reagent batches.
Normalization	Sample‐wide adjustment of the data with the intention to bring the distribution of measured quantities into alignment. Most prominently, sample means and medians are aligned after normalization.
Batch effect correction	Data transformation procedure that corrects quantities of specific features (genes, peptides, metabolites) across samples, to reduce differences that are associated with technical factors, recorded in the experimental protocol (i.e., sample preparation or measurement batches). Usually samples are assumed to be normalized prior to batch effect correction. This step is often called "batch effect removal" or "batch effect adjustment" in the literature. Note the difference in the definition used here.
Batch effect adjustment	Data transformation procedure that adjusts for differences between samples due to technical factors that altered the data (sample‐wise and/or feature‐wise). The fundamental objective of the batch effect adjustment is to make all samples comparable for a meaningful biological analysis. In our definition, batch effect adjustment is a two‐step transformation: first normalization, then batch effect correction. Performing normalization first helps feature‐level batch effect correction by first alleviating sample level discrepancies.