ena-database

What it does

The skill instructs an AI agent to interact with the ENA REST APIs to search and retrieve metadata and data across ENA data types, including studies, samples, read runs, assemblies, and cross-references. It includes examples of browsing records in multiple formats (XML, FASTA, EMBL), obtaining file reports with download URLs for FASTQ/BAM, and looking up taxonomy information. It emphasizes using appropriate Python modules for multi-database queries and provides quick-start code and workflows for study exploration, bulk FASTQ URL collection, and taxonomic assembly exploration.

How it works

• Use Portal API to perform advanced metadata searches across ENA data types, with fields, pagination, and JSON/TSV/XML formats.
• Use Browser API to retrieve individual records by accession in XML, FASTA, EMBL, or plain text formats.
• Use filereport to obtain download URLs for FASTQ/other files, including parsing fastq_ftp and fastq_md5 fields.
• Use taxonomy endpoints to lookup taxa by ID, scientific name, or partial matches, and suggest organisms.
• Use xref endpoints to find cross-references between ENA records and external databases.
• Include rate-limit handling (50 requests per second) and pagination strategies, plus example code snippets.
• Provide workflows for study exploration, bulk FASTQ URL collection, and taxonomic assembly exploration, including step-by-step programmatic actions and required fields.
• List prerequisites such as pip install requests and describe endpoint bases and common fields.

When to use it

• When searching for sequencing studies, samples, or experiments by organism or keyword.
• When downloading raw FASTQ/BAM files for reanalysis.
• When retrieving genome assemblies and quality statistics.
• When fetching nucleotide sequences in FASTA or EMBL formats by accession.
• When exploring taxonomic lineage or finding organisms by partial names.
• When cross-referencing ENA records with external databases.
• When building bulk download lists for large projects.
• If integrating with multiple databases in Python, prefer bioservices; for NCBI-specific queries, use pubmed-database or Biopython Entrez.

What it can touch

• Portal API: https://www.ebi.ac.uk/ena/portal/api
• Browser API: https://www.ebi.ac.uk/ena/browser/api
• Taxonomy API: https://www.ebi.ac.uk/ena/taxonomy/rest
• Cross-ref API: https://www.ebi.ac.uk/ena/xref/rest
• File reports via filereport endpoint (e.g., accessions like ERR000589)
• It uses standard Python tooling (requests) as shown in examples.

Caveats

• API constraints: Rate limit of 50 requests per second across all ENA APIs; no authentication required.
• Large result sets require pagination or streaming (limit/offset or limit=0).
• Some fields and endpoints may change; examples use current endpoint structures and field names (e.g., run_accession, sample_accession, fastq_ftp, fastq_md5).
• License is NOASSERTION per the metadata; real-world use should verify licensing if redistributing data.