Digital expression explorer 2: a repository of uniformly processed RNA sequencing data.
BACKGROUND
RNA sequencing (RNA-seq) is an indispensable tool in the study of gene regulation. While the technology has brought with it better transcript coverage and quantification, there remain considerable barriers to entry for the computational biologist to analyse large data sets. There is a real need for a repository of uniformly processed RNA-seq data that is easy to use.


FINDINGS
To address these obstacles, we developed Digital Expression Explorer 2 (DEE2), a web-based repository of RNA-seq data in the form of gene-level and transcript-level expression counts. DEE2 contains >5.3 trillion assigned reads from 580,000 RNA-seq data sets including species Escherichia coli, yeast, Arabidopsis, worm, fruit fly, zebrafish, rat, mouse, and human. Base-space sequence data downloaded from the National Center for Biotechnology Information Sequence Read Archive underwent quality control prior to transcriptome and genome mapping using open-source tools. Uniform data processing methods ensure consistency across experiments, facilitating fast and reproducible meta-analyses.


CONCLUSIONS
The web interface allows users to quickly identify data sets of interest using accession number and keyword searches. The data can also be accessed programmatically using a specifically designed R package. We demonstrate that DEE2 data are compatible with statistical packages such as edgeR or DESeq. Bulk data are also available for download. DEE2 can be found at http://dee2.io.
['Ziemann|Mark|M|', 'Kaspi|Antony|A|', 'El-Osta|Assam|A|']
D019295:Computational Biology D020869:Gene Expression Profiling D059014:High-Throughput Nucleotide Sequencing D015201:Meta-Analysis as Topic D011786:Quality Control D015203:Reproducibility of Results D017423:Sequence Analysis, RNA D012984:Software D059467:Transcriptome D057188:Workflow
RNA-seq transcriptome data reuse gene expression