Related Experiment Videos
The RNASeq-er API-a gateway to systematically updated analysis of public RNA-seq data
Robert Petryszak1, Nuno A Fonseca1, Anja Füllgrabe1
1Functional Genomics Group, European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK.
Bioinformatics (Oxford, England)
|April 4, 2017
Summary
Researchers can now easily access and analyze vast amounts of public RNA-sequencing (RNA-Seq) data through the new RNASeq-er API. This web service provides standardized gene expression quantification and alignment data for 264 species, simplifying complex data management for all scientists.
Area of Science:
- Bioinformatics
- Genomics
- Computational Biology
Background:
- Exponential growth of public RNA-sequencing (RNA-Seq) data presents significant challenges for researchers regarding data discovery, analysis, and storage, especially for institutions with limited computational resources.
- The European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI) is well-positioned to address these challenges by providing accessible processed RNA-Seq data.
Purpose of the Study:
- To present a web service for accessing systematically updated, standardized RNA-sequencing data.
- To enable researchers to discover, analyze, and store large RNA-Seq datasets efficiently.
- To provide access to processed RNA-Seq data, including alignment and gene/exon expression quantification.
Main Methods:
- Development of the RNASeq-er Application Programming Interface (API) using Representational State Transfer (REST).
- Systematic and continuous processing of all public bulk RNA-sequencing runs in 264 species available in the European Nucleotide Archive (ENA).
- Standardized alignment and gene/exon expression quantification (Fragments Per Kilobase Of Exon Per Million Fragments Mapped, Transcripts Per Million, raw counts).
Main Results:
- The RNASeq-er API provides access to processed RNA-Seq data for 264 species, including CRAM, bigwig, and bedGraph files.
- Over 270,000 RNA-Seq runs from nearly 10,000 studies (1 Petabyte of raw FASTQ data) have been processed and made available via the API.
- The API supports ontology-powered search and retrieval of sample attributes and quantification matrices.
Conclusions:
- The RNASeq-er API offers a valuable resource for the scientific community, simplifying access to and analysis of large-scale RNA-Seq data.
- This service democratizes access to processed RNA-Seq data, empowering researchers regardless of their institutional computational resources.
- Future development will include the integration of single-cell RNA-Seq data.