Researchers from the LBI and the University Vienna now made a fast and simple tool for the assessment of RNA-Seq normalization strategies avaialble. They describe their approach in a recent paper in the journal bioinformatics.
Measuring differential gene expression is a common task in the analysis of RNA-Seq data, the method of choice to analyse differential gene-expression. Normalization of datasets is a crucial step to make data comparable. 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. Therefore the NVT package provides a fast and simple way to analyze and evaluate multiple normalization methods via visualization and representation of correlation values, based on a userdefined set of uniformly expressed genes. The R package is freely available here.