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CONSTANd: An Efficient Normalization Method for Relative Quantification in Small- and Large-Scale Omics Experiments in R BioConductor and Python.
Van Houtven, Joris; Hooyberghs, Jef; Laukens, Kris; Valkenborg, Dirk.
Afiliación
  • Van Houtven J; Flemish Institute for Technological Research (VITO), Boeretang 200, B-2400 Mol, Belgium.
  • Hooyberghs J; Data Science Institute (DSI), Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Universiteit Hasselt, Agoralaan, Diepenbeek 3590, Belgium.
  • Laukens K; Adrem Data Lab, Department of Computer Sciences, Universiteit Antwerpen, Middelheimlaan 1, Antwerpen 2020, Belgium.
  • Valkenborg D; Flemish Institute for Technological Research (VITO), Boeretang 200, B-2400 Mol, Belgium.
J Proteome Res ; 20(4): 2151-2156, 2021 04 02.
Article en En | MEDLINE | ID: mdl-33703904
ABSTRACT
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.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Programas Informáticos / Boidae Límite: Animals Idioma: En Revista: J Proteome Res Asunto de la revista: BIOQUIMICA Año: 2021 Tipo del documento: Article País de afiliación: Bélgica

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Programas Informáticos / Boidae Límite: Animals Idioma: En Revista: J Proteome Res Asunto de la revista: BIOQUIMICA Año: 2021 Tipo del documento: Article País de afiliación: Bélgica