Related Experiment Video
Updated: Jul 29, 2025

Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
Published on: September 18, 2021
NORMSEQ: a tool for evaluation, selection and visualization of RNA-Seq normalization methods
Chantal Scheepbouwer1,2,3, Michael Hackenberg4,5,6,7, Monique A J van Eijndhoven3,8
1Department of Neurosurgery, Cancer Center Amsterdam, Amsterdam University Medical Center (UMC) location Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands.
Abstract:
RNA-sequencing has become one of the most used high-throughput approaches to gain knowledge about the expression of all different RNA subpopulations. However, technical artifacts, either introduced during library preparation and/or data analysis, can influence the detected RNA expression levels. A critical step, especially in large and low input datasets or studies, is data normalization, which aims at eliminating the variability in data that is not related to biology. Many normalization methods have been developed, each of them relying on different assumptions, making the selection of the appropriate normalization strategy key to preserve biological information. To address this, we developed NormSeq, a free web-server tool to systematically assess the performance of normalization methods in a given dataset. A key feature of NormSeq is the implementation of information gain to guide the selection of the best normalization method, which is crucial to eliminate or at least reduce non-biological variability. Altogether, NormSeq provides an easy-to-use platform to explore different aspects of gene expression data with a special focus on data normalization to help researchers, even without bioinformatics expertise, to obtain reliable biological inference from their data. NormSeq is freely available at: https://arn.ugr.es/normSeq.

