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

Journal Contribution - Journal Article

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.
Journal: JOURNAL OF PROTEOME RESEARCH
ISSN: 1535-3893
Issue: 4
Volume: 20
Pages: 2151 - 2156
Publication year:2021
Keywords:normalization, transcriptomics, quantitative, proteomics, mass spectrometry, data-driven, multiomics, workflow, quality control
BOF-keylabel:yes
IOF-keylabel:yes
BOF-publication weight:1
Authors from:Government, Higher Education, Private
Accessibility:Open