bio-splicing-pipeline

Identify and quantify differential alternative splicing events from RNA-seq data.

Updated Mar 30, 2026
One-click install
npx skills add https://github.com/ya-way/cytoclaw-skills --skill bio-splicing-pipeline
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bio-splicing-pipeline
Source: https://github.com/ya-way/cytoclaw-skills/tree/main/workspace/skills/bio-wf-splicing-pipeline
Command: npx skills add https://github.com/ya-way/cytoclaw-skills --skill bio-splicing-pipeline

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

End-to-end splicing analysis from RNA-seq data, orchestrating alignment, junction QC, differential splicing testing, and visualization to deliver reliable results with reproducible workflows.

Core Features & Use Cases

  • STAR 2-pass alignment for improved junction discovery and quantification
  • Differential splicing analysis with rMATS-turbo and optional IsoformSwitchAnalyzeR
  • Sashimi plot visualization and standard reporting for publication-ready results
  • Use Case: Analyze a multi-condition RNA-seq experiment to identify condition-specific splice events and visualize top candidates

Quick Start

Run a complete splicing analysis on a set of RNA-seq FASTQ files, producing differential splicing results and sashimi plots.

Frequently Asked Questions about bio-splicing-pipeline

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

FAQPage Schema
How do I identify differential alternative splicing events from RNA-seq FASTQ files?▼

You can perform differential splicing analysis with rMATS-turbo directly on RNA-seq FASTQ files. The pipeline handles STAR 2-pass alignment and junction quality control automatically before running the differential testing.

What is the best way to run junction saturation checks for alternative splicing analysis?▼

The best way to run junction saturation checks for alternative splicing analysis is through an end-to-end pipeline that integrates quality control after STAR 2-pass alignment. This ensures robust junction discovery and quantification before differential testing.

Can I generate Sashimi plots for condition-specific splice events from RNA-seq data?▼

Yes, you can generate Sashimi plots for condition-specific splice events from RNA-seq data. The pipeline produces Sashimi plot visualizations and standardized reports for publication-ready results after identifying top differential splicing candidates.

Does this RNA-seq splicing analysis pipeline support IsoformSwitchAnalyzeR?▼

Yes, this RNA-seq splicing analysis pipeline supports optional IsoformSwitchAnalyzeR analysis. It integrates this tool alongside rMATS-turbo differential testing to generate robust results and support downstream interpretation.

Do I need aligned BAM files or raw FASTQ files for rMATS-turbo differential splicing testing?▼

You can use raw FASTQ files for rMATS-turbo differential splicing testing because the pipeline performs STAR 2-pass alignment first. It processes FASTQ inputs end-to-end to produce standardized outputs for reproducibility.

Why use STAR 2-pass alignment for alternative splicing quantification?▼

STAR 2-pass alignment is used for alternative splicing quantification to improve junction discovery and accuracy. It maps RNA-seq reads across splice junctions more comprehensively before rMATS-turbo tests for differential events.