A note on an exon-based strategy to identify differentially expressed genes in RNA-seq experiments.

ABSTRACT: RNA-sequencing (RNA-seq) has rapidly become the method of choice in many genome-wide transcriptomic studies. To meet the high expectations posed by this technology, powerful computational techniques are needed to translate the measurements into biological and biomedical understanding. A number of statistical procedures have already been developed to identify differentially expressed genes between distinct sample groups. With these methods statistical testing is typically performed after the data has been summarized at the gene level. As an alternative strategy, developed with the aim to improve the results, we demonstrate a method in which statistical testing at the exon level is performed prior to the summary of the results at the gene level. Using publicly available RNA-seq datasets as c

SUBMITTER: Laiho A 

PROVIDER: S-EPMC4277429 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature