NVT: a fast and simple tool for the assessment of RNA-seq normalization strategies

Bioinformatics. 2016 Dec 1;32(23):3682-3684. doi: 10.1093/bioinformatics/btw521. Epub 2016 Aug 11.


Motivation: Measuring differential gene expression is a common task in the analysis of RNA-Seq data. To identify differentially expressed genes between two samples, it is crucial to normalize the datasets. While multiple normalization methods are available, all of them are based on certain assumptions that may or may not be suitable for the type of data they are applied on. Researchers therefore need to select an adequate normalization strategy for each RNA-Seq experiment. This selection includes exploration of different normalization methods as well as their comparison. Methods that agree with each other most likely represent realistic assumptions under the particular experimental conditions.

Results: We developed the NVT package, which provides a fast and simple way to analyze and evaluate multiple normalization methods via visualization and representation of correlation values, based on a user-defined set of uniformly expressed genes.

Availability and implementation: The R package is freely available under https://github.com/Edert/NVT CONTACT: thomas.rattei@univie.ac.atSupplementary information: Supplementary data are available at Bioinformatics online.

MeSH terms

  • Computational Biology / methods
  • Humans
  • RNA / genetics*
  • Sequence Analysis, RNA / methods*
  • Software*


  • RNA