MOTIVATION: The exponential growth of publicly available RNA-sequencing (RNA-Seq) data poses an increasing challenge to researchers wishing to discover, analyse and store such data, particularly those based in institutions with limited computational resources. EMBL-EBI is in an ideal position to address these challenges and to allow the scientific community easy access to not just raw, but also processed RNA-Seq data. We present a Web service to access the results of a systematically and continually updated standardized alignment as well as gene and exon expression quantification of all public bulk (and in the near future also single-cell) RNA-Seq runs in 264 species in European Nucleotide Archive, using Representational State Transfer. RESULTS: The RNASeq-er API (Application Programming Interface) enables ontology-powered search for and retrieval of CRAM, bigwig and bedGraph files, gene and exon expression quantification matrices (Fragments Per Kilobase Of Exon Per Million Fragments Mapped, Transcripts Per Million, raw counts) as well as sample attributes annotated with ontology terms. To date over 270 00 RNA-Seq runs in nearly 10 000 studies (1PB of raw FASTQ data) in 264 species in ENA have been processed and made available via the API. AVAILABILITY AND IMPLEMENTATION: The RNASeq-er API can be accessed at http://www.ebi.ac.uk/fg/rnaseq/api . The commands used to analyse the data are available in supplementary materials and at https://github.com/nunofonseca/irap/wiki/iRAP-single-library . CONTACT: [email protected] ; [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: There is accumulating evidence that the milieu of repeat elements and other non-genic sequence features at a given chromosomal locus, here defined as the genome environment, can play an important role in regulating chromosomal processes such as transcription, replication and recombination. The availability of whole-genome sequences has allowed us to annotate the genome environment of any locus in detail. The development of genome wide experimental analyses of gene expression, chromatin modification and chromatin proteins means that it is now possible to identify potential links between chromosomal processes and the underlying genome environment. There is a need for novel bioinformatic tools that facilitate these studies. RESULTS: We developed the Genome Environment Browser (GEB) in order to visualise the integration of experimental data from large scale high throughput analyses with repeat sequence features that define the local genome environment. The browser has incorporated dynamic scales adjustable in real-time, which enables scanning of large regions of the genome as well as detailed investigation of local regions on the same page without the need to load new pages. The interface also accommodates a 2-dimensional display of repetitive features which vary substantially in size, such as LINE-1 repeats. Specific queries for preliminary quantitative analysis of genome features can also be formulated, results of which can be exported for further analysis. CONCLUSION: The Genome Environment Browser is a versatile program which can be easily adapted for displaying all types of genome data with known genomic coordinates. It is currently available at http://web.bioinformatics.ic.ac.uk/geb/.