sdrf:explain

Explain SDRF column definitions, format rules, and validation errors for proteomics metadata.

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Helps researchers and annotators understand SDRF columns, error messages, and format rules so they can produce valid, analysis-ready proteomics metadata and avoid common annotation mistakes.

Core Features & Use Cases

  • Column explanations: Translate spec entries into plain-language definitions, why each column matters, expected types, allowed values, and reserved words based on the SDRF specification.
  • Error diagnosis and fixes: Explain validation errors, identify the violated rule, propose exact edits to correct values, and recommend prevention strategies.
  • Contextual examples and guidance: Provide real-world proteomics examples, distinctions between characteristics/comment/factor value, and links back to templates and ontology usage for PRIDE submissions and dataset curation.

Quick Start

Ask the skill to explain the purpose, format rules, and example values for the column characteristics[biological replicate].

Frequently Asked Questions about sdrf:explain

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

FAQPage Schema
What is an SDRF file and why is it needed for proteomics metadata annotation?

An SDRF file structures proteomics metadata for reproducible annotation and PRIDE submissions. It defines experimental variables, characteristics, and factor values so downstream tools can correctly interpret sample attributes and experimental design.

How do I fix validation errors in my SDRF file?

To fix SDRF validation errors, identify the violated rule, correct the specific column value, and check ontology terms against the specification. Common fixes involve correcting reserved words, updating characteristics columns, and ensuring proper factor value formatting.

What is the difference between characteristics, comment, and factor value columns in SDRF?

Characteristics describe inherent sample properties, comments add free-text metadata, and factor values represent experimental variables. SDRF annotation distinguishes these to ensure downstream analysis correctly separates biological attributes from experimental design factors.

How do I select the right SDRF template for my proteomics experiment?

Select an SDRF template by matching your experimental design to the specification's defined templates. The right template provides required columns, expected ontology terms, and format rules, ensuring valid PRIDE submissions and reproducible dataset curation.

Can I use custom ontology terms in SDRF columns for PRIDE submissions?

SDRF column annotation requires controlled vocabulary and ontology terms recognized by the specification. Using custom terms triggers validation errors; you must select valid ontology terms from approved sources to ensure successful PRIDE submissions and reproducible annotation.

Why does my SDRF validation fail on biological replicate columns?

SDRF validation fails on biological replicate columns when values violate formatting rules, use reserved words incorrectly, or lack required ontology terms. Correct the column by applying exact expected value types and plain-language definitions from the SDRF specification.