drop

Community

Detect RNA outliers from sequencing data

Authordanilomonge
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill helps you run the DROP nf-core pipeline without manual schema hunting, so you can analyze RNA sequencing data for aberrant expression, aberrant splicing, and mono-allelic expression with the correct parameters and outputs.

Core Features & Use Cases

  • End-to-End RNA Outlier Detection: Executes a production-ready workflow for RNA outlier discovery across expression, splicing, and allele-specific signals.
  • Samplesheet-Driven Runs: Supports different input modes such as BAM or CRAM based samples, gene counts with annotations, or splice count directories.
  • Validated Pipeline Configuration: Surfaces required inputs, optional analysis groups, genome settings, and release-specific flags so runs stay reproducible and schema-compliant.

Quick Start

Ask the assistant to run the DROP pipeline on your samplesheet with the right genome, output directory, and sequencing input type for your dataset.

Dependency Matrix

Required Modules

None required

Components

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: drop
Download link: https://github.com/danilomonge/nf-claw/archive/main.zip#drop

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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