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

• Published in: Briefings in bioinformatics Vol. 14; no. 6; pp. 671 - 683
• Main Authors: Dillies, M.-A., Rau, A., Aubert, J., Hennequet-Antier, C., Jeanmougin, M., Servant, N., Keime, C., Marot, G., Castel, D., Estelle, J., Guernec, G., Jagla, B., Jouneau, L., Laloe, D., Le Gall, C., Schaeffer, B., Le Crom, S., Guedj, M., Jaffrezic, F.
• Format: Journal Article
• Language: English
• Published: England Oxford Publishing Limited (England) 01.11.2013; Oxford University Press (OUP)
• Subjects: Applications; Bias; Biochemistry, Molecular Biology; Bioinformatics; Comparative analysis; Genomics; High-Throughput Nucleotide Sequencing - methods; High-Throughput Nucleotide Sequencing - standards; Life Sciences; Methodology; Ribonucleic acid; RNA; Sequence Analysis, RNA - methods; Sequence Analysis, RNA - standards; Simulation; Statistics; differential analysis; RNA-seq; normalization; high-throughput sequencing

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 approp...