Typically, RNA-Seq reads are classified based on their mapping to a common region of the target genome such as exon or transcript. One of the fundamental data analysis tasks for RNA-seq studies is to determine whether there is evidence that read counts for a transcript or gene are significantly different across experimental conditions. At present, there are three major algorithms to address this.
EdgeR, DESeq and bayseq are available as R packages, to compare sequencing reads and to identify significantly expressed transcripts or genes. For these bioinformatics packages, users have to manually install and run each separately.
Here, the authors present a pipeline, DEB which automates all the steps in file preparation, computation and result comparison.
Availability: DEB is freely accessed at http://www.ijbcb.org/DEB/php/onlinetool.php
- Yao JQ, Yu F. (2011) DEB: A web interface for RNA-seq digital gene expression analysis. Bioinformation 7(1), 44-45. [abstract]