sdrf:annotate

Generate SDRF files for proteomics datasets from PXD accessions.

11|9|Updated Mar 18, 2026
One-click install
npx skills add https://github.com/bigbio/sdrf-skills --skill sdrf-annotate
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: sdrf:annotate
Source: https://github.com/bigbio/sdrf-skills/tree/main/skills/sdrf-annotate
Command: npx skills add https://github.com/bigbio/sdrf-skills --skill sdrf-annotate

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Researchers and curators must create highly accurate SDRF files for proteomics datasets, a process that involves complex template selection, ontology term lookup, and detailed technical metadata extraction from PRIDE and raw files.

Core Features & Use Cases

  • End‑to‑end workflow: Guides users from PXD accession or experiment description through template selection, sample and technical metadata collection, file‑sample mapping, and validation.
  • Ontology integration: Searches OLS for precise organism, disease, cell type, and modification terms, ensuring compliance with SDRF standards.
  • Automated validation: Generates a temporary SDRF file and runs parse_sdrf validation against selected templates, fixing errors before delivery.
  • Community contribution: Offers optional steps to submit the final SDRF back to the proteomics‑sample‑metadata repository.

Quick Start

Ask the assistant to create an SDRF for a ProteomeXchange dataset by providing its PXD identifier, e.g., “Create an SDRF for PXD012345”.

Frequently Asked Questions about sdrf:annotate

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create an SDRF file for a ProteomeXchange dataset?

To create an SDRF file for a ProteomeXchange dataset, provide the PXD accession identifier to the assistant. The workflow then coordinates template selection, ontology lookup, and technical metadata extraction from PRIDE to generate the file.

What is SDRF annotation for proteomics experiments?

SDRF annotation is the process of generating structured metadata files for proteomics datasets. It involves selecting templates, looking up ontology terms via OLS, and extracting technical metadata to ensure compliance with community standards.

How do I validate an SDRF file before submission?

You validate an SDRF file by generating a temporary file and running the parse_sdrf validation tool against selected templates. This process identifies and fixes formatting or ontology errors before final delivery.

Can I use literature descriptions instead of PXD accessions to generate proteomics metadata?

Yes, you can use literature descriptions and raw file metadata instead of PXD accessions. The workflow accepts experiment descriptions to guide template selection and sample metadata collection for the SDRF file.

Does SDRF annotation require ontology term lookups for cell type and disease?

Yes, SDRF annotation requires ontology term lookups for cell type, disease, organism, and modifications. The workflow searches the OLS ontology lookup service to ensure precise terminology and SDRF standard compliance.

What are the limitations when creating SDRF files for raw proteomics data?

Creating SDRF files is limited by the need for accessible PRIDE APIs for project metadata and OLS for ontology terms. Without access to these external services, the automated template selection and validation workflow cannot function correctly.