sdrf:design
OfficialAnalyze SDRF design for batch effects & confounds
Data & Analytics#design-analysis#batch-effects#msstats#sdrf#confounder-detection#replication-assessment
Authorbigbio
Version1.0.0
Installs0
System Documentation
What problem does it solve?
The skill helps users assess the experimental design captured in an SDRF file, identifying batch effects, confounding variables, and replication issues that can compromise downstream analysis.
Core Features & Use Cases
- Design Summary: Extracts conditions, replicates, instruments, and file counts to produce a concise overview.
- Confounder Detection: Cross‑tabulates factor values against technical variables (instrument, TMT labels, processing dates) to flag perfect or partial confounds.
- Replication Assessment: Evaluates biological and technical replicate counts and suggests statistical power.
- Comparison Guidance: Generates recommended contrast matrices for tools like MSstats.
- Use Case: A proteomics researcher uploads an SDRF for a breast cancer vs. normal study and receives a detailed design report highlighting any batch‑effect risks and suggested contrasts.
Quick Start
Ask the skill to analyze your SDRF file and provide a design report.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: sdrf:design Download link: https://github.com/bigbio/sdrf-skills/archive/main.zip#sdrf-design Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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