The Impact of Normalization Methods on RNA-Seq Data Analysis.

ABSTRACT: High-throughput sequencing technologies, such as the Illumina Hi-seq, are powerful new tools for investigating a wide range of biological and medical problems. Massive and complex data sets produced by the sequencers create a need for development of statistical and computational methods that can tackle the analysis and management of data. The data normalization is one of the most crucial steps of data processing and this process must be carefully considered as it has a profound effect on the results of the analysis. In this work, we focus on a comprehensive comparison of five normalization methods related to sequencing depth, widely used for transcriptome sequencing (RNA-seq) data, and their impact on the results of gene expression analysis. Based on this study, we suggest a universal work

SUBMITTER: Zyprych-Walczak J 

PROVIDER: S-EPMC4484837 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature