An integrative method to normalize RNA-Seq data.

ABSTRACT:

Background

Transcriptome sequencing is a powerful tool for measuring gene expression, but as well as some other technologies, various artifacts and biases affect the quantification. In order to correct some of them, several normalization approaches have emerged, differing both in the statistical strategy employed and in the type of corrected biases. However, there is no clear standard normalization method.

Results

We present a novel methodology to normalize RNA-Seq data, taking into account transcript size, GC content, and sequencing depth, which are the major quantification-related biases. In this study, we found that transcripts shorter than 600 bp have an underestimated expression level, while longer transcripts are even more overestimated that they are long. Second, it w

SUBMITTER: Filloux C 

PROVIDER: S-EPMC4067528 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature