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bio-workflows-rnaseq-to-de

Automates RNA-seq pipeline from FASTQ files to differential expression with DESeq2 and Salmon or STAR+featureCounts.

Updated Feb 3, 2026
Search Tags:#bioinformatics#differential expression#rna-seq#star#deseq2#fastq#salmon
One-click install
npx skills add https://github.com/Revelo-RNASeq/2025_RNASeq --skill bio-workflows-rnaseq-to-de
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bio-workflows-rnaseq-to-de
Source: https://github.com/Revelo-RNASeq/2025_RNASeq/tree/main/.agents/skills/bio-workflows-rnaseq-to-de
Command: npx skills add https://github.com/Revelo-RNASeq/2025_RNASeq --skill bio-workflows-rnaseq-to-de

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires fastp, salmon, star, featurecounts, deseq2, tximport, pypdf, pdfplumber, pdf2image, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the complex process of analyzing RNA sequencing data, transforming raw FASTQ files into actionable differential expression results, thereby streamlining genomic research.

Core Features & Use Cases

  • End-to-End Workflow: Manages the entire RNA-seq analysis pipeline from raw reads to identifying significant gene expression changes.
  • Flexible Quantification: Supports both alignment-free (Salmon) and alignment-based (STAR + featureCounts) quantification methods.
  • Robust DE Analysis: Utilizes DESeq2 for statistically sound differential expression analysis.
  • Visualization: Generates key plots like volcano plots and heatmaps for result interpretation.
  • Use Case: Researchers can use this Skill to quickly process their RNA-seq experiments, compare gene expression between different conditions (e.g., treated vs. control), and identify potential biomarkers or therapeutic targets.

Quick Start

Run the RNA-seq to DE workflow on my FASTQ files.

Frequently Asked Questions about bio-workflows-rnaseq-to-de

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

FAQPage Schema
How do I run a complete RNA-seq differential expression pipeline from FASTQ files?▼

To run an RNA-seq differential expression pipeline, this workflow automates the entire process from raw FASTQ files to DE results. It performs quality control with fastp, quantifies reads via Salmon or STAR+featureCounts, and conducts DE analysis using DESeq2.

Salmon vs STAR for RNA-seq quantification: which method should I use for differential expression?▼

For RNA-seq quantification, Salmon provides alignment-free transcript quantification, while STAR plus featureCounts offers alignment-based gene-level counting. Both methods integrate seamlessly with DESeq2 via tximport to produce differential expression results.

Do I need to run fastp for quality control before DESeq2 differential expression analysis?▼

Yes, fastp is integrated directly into the workflow to handle quality control of your FASTQ files before quantification. This ensures that only high-quality reads proceed to Salmon or STAR alignment and subsequent DESeq2 analysis.

Can I generate volcano plots and heatmaps from RNA-seq differential expression results?▼

Yes, the workflow generates volcano plots and heatmaps automatically from your differential expression results. These visualizations help interpret significant gene expression changes between conditions like treated and control samples.

What is the best way to identify significant gene expression changes between treated and control samples?▼

The best way to identify significant gene expression changes is using DESeq2 for robust statistical differential expression analysis. This workflow processes treated and control FASTQ files through quantification and DESeq2 to pinpoint potential biomarkers.

Does this RNA-seq pipeline support alignment-free transcript quantification with Salmon?▼

Yes, the RNA-seq pipeline supports alignment-free transcript quantification using Salmon. It uses tximport to import Salmon transcript counts into DESeq2 for comprehensive differential expression analysis.

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