Title :

A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis

Author(s) :

Dillies, Marie-Agnès [Auteur]
Puces à ADN (Plate-Forme 2) [PF2]
Rau, Andrea [Auteur]
Génétique Animale et Biologie Intégrative [GABI]
Aubert, Julie [Auteur]
Mathématiques et Informatique Appliquées [MIA-Paris]
Hennequet-Antier, Christelle [Auteur]
Centre Médical de l'Institut Pasteur [CMIP]
Jeanmougin, Marine [Auteur]
Laboratoire Statistique et Génome [LSG]
Servant, Nicolas [Auteur]
Cancer et génome: Bioinformatique, biostatistiques et épidémiologie d'un système complexe
Keime, Céline [Auteur]
Institut de Génétique et de Biologie Moléculaire et Cellulaire [IGBMC]
Marot, Guillemette [Auteur]
Evaluation des technologies de santé et des pratiques médicales - ULR 2694 [METRICS]
MOdel for Data Analysis and Learning [MODAL]
Castel, David [Auteur]
Laboratoire d'Exploration Fonctionnelle des Génomes [LEFG]
Estellé, Jordi [Auteur]
Centro Nacional de Análisi Genómico [CNAG]
Guernec, Grégory [Auteur]
Epidémiologie des maladies infectieuses et modélisation [ESIM]
Jagla, Bernd [Auteur]
Centre Médical de l'Institut Pasteur [CMIP]
Jouneau, Luc [Auteur]
INRA - Mathématiques et Informatique Appliquées [Unité MIAJ]
Laloë, Denis [Auteur]
Génétique Animale et Biologie Intégrative [GABI]
Le Gall, Caroline [Auteur]
Schaeffer, Brigitte [Auteur]
Le Crom, Stéphane [Auteur]
GenomiqueENS [Genomique ENS]
Guedj, Mickaël [Auteur]
Jaffrezic, Florence [Auteur]
Génétique Animale et Biologie Intégrative [GABI]

Journal title :

Briefings in Bioinformatics

Pages :

671-683

Publisher :

Oxford University Press (OUP)

Publication date :

2012

ISSN :

1467-5463

English keyword(s) :

high-throughput sequencing
differential analysis
RNA-seq
normalization

HAL domain(s) :

Statistiques [stat]/Applications [stat.AP]
Sciences du Vivant [q-bio]
Sciences du Vivant [q-bio]/Biochimie, Biologie Moléculaire/Génomique, Transcriptomique et Protéomique [q-bio.GN]
Statistiques [stat]/Méthodologie [stat.ME]

English abstract : [en]

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, ...
Show more >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 in practice. Based on this comparison study, we propose practical recommendations on the appropriate normalization method to be used and its impact on the differential analysis of RNA-seq data.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Comment :

The French StatOmique Consortium gathers more than 40 statisticians and bioinformaticians involved in high-throughput transcriptome data analysis in France. The objective of this group, created in 2008, is to share among researchers and practitioners knowledge of the statistical analysis of high-throughput data. Chantier qualité GA

Collections :

• Laboratoire Paul Painlevé - UMR 8524

Source :

Harvested from HAL