CONSTANd: An Efficient Normalization Method for Relative Quantification in Small- and Large-Scale Omics Experiments in R BioConductor and Python

For differential expression studies
in all omics disciplines, data
normalization is a crucial step that is often subject to a balance
between speed and effectiveness. To keep up with the data produced
by high-throughput instruments, researchers require fast and easy-to-use
yet effective methods that fit into automated analysis pipelines.
The CONSTANd normalization method meets these criteria, so we have
made its source code available for R/BioConductor and Python. We briefly
review the method and demonstrate how it can be used in different
omics contexts for experiments of any scale. Widespread adoption across
omics disciplines would ease data integration in multiomics experiments.