A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis
Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement · Génétique Animale et Biologie Intégrative · +13 more institutions
Abstract
During the last 3 years, a number of approaches for the normalization of RNA sequencing data have emerged in the literature, differing both in the type of bias adjustment and in the statistical strategy adopted. However, as data continue to accumulate, there has been no clear consensus on the appropriate normalization method to be used or the impact of a chosen method on the downstream analysis. In this work, we focus on a comprehensive comparison of seven recently proposed normalization methods for the differential analysis of RNA-seq data, with an emphasis on the use of varied real and simulated datasets involving different species and experimental designs to represent data characteristics commonly observed…
Citation impact
- FWCI
- 36.00
- Percentile
- 100%
- References
- 50
Authors
19- MDMarie‐Agnès DilliesCorresponding
- ARAndréa Rau
Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Génétique Animale et Biologie Intégrative
- JAJulie Aubert
Université Claude Bernard Lyon 1, Département mathématiques, informatique, sciences de la donnée et technologies du numérique, Mathématiques et Informatique Appliquées
- CHChristelle Hennequet‐Antier
Institut Pasteur
- MJMarine Jeanmougin
Topics & keywords
- Normalization (sociology)
- Computer science
- RNA-Seq
- Data mining
- RNA
- Computational biology
- Biology
- Gene