drop
CommunityDetect RNA outliers from sequencing data
Education & Research#bioinformatics#nf-core#nextflow#rna-seq#outlier detection#splicing#monoallelic expression
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 requiredComponents
Standard package💻 Claude Code Installation
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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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