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rna-quantification

Quantify gene and transcript abundances from RNA-seq reads using salmon, kallisto, or featureCounts.

25|5|Updated Mar 22, 2026
Search Tags:#rna-seq#quantification#qc#kallisto#salmon#gene-counts#transcript-abundances
One-click install
npx skills add https://github.com/zongtingwei/Bioclaw_Skills_Hub --skill rna-quantification
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: rna-quantification
Source: https://github.com/zongtingwei/Bioclaw_Skills_Hub/tree/main/skills/transcriptomics/rna-quantification
Command: npx skills add https://github.com/zongtingwei/Bioclaw_Skills_Hub --skill rna-quantification

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

RNA-quantification workflows automate the process of converting RNA-seq reads into gene-level counts and transcript-level abundances, enabling downstream analyses and reporting with reproducible steps.

Core Features & Use Cases

  • Supports alignment-based and alignment-free quantification to accommodate different data and pipelines.
  • Generates gene counts, transcript abundances, and QC summaries for reliable downstream analyses.
  • Use Case: When you need expression estimates for differential expression or tximport-style workflows, this skill provides a complete quantification path.

Quick Start

Run the quantification workflow on RNA-seq data using salmon or kallisto to generate gene counts and transcript abundances.

Frequently Asked Questions about rna-quantification

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

FAQPage Schema
How do I quantify RNA-seq gene and transcript abundances from FASTQ files?▼

To quantify RNA-seq abundances, you process FASTQ files using alignment-based or alignment-free methods like salmon or kallisto, producing gene counts, transcript abundances, and QC summaries.

What is the difference between alignment-based and alignment-free RNA-seq quantification?▼

Alignment-based quantification maps reads to a reference genome before counting, while alignment-free methods like salmon and kallisto estimate transcript abundances directly against a transcriptome, both yielding gene counts and abundances.

Do I need a reference genome and GTF annotation to generate gene counts?▼

Yes, generating gene counts typically requires a reference genome or transcriptome alongside GTF or GFF annotation files to map reads and summarize transcript abundances into gene-level estimates.

Can I use kallisto and salmon for tximport-style differential expression workflows?▼

Yes, both kallisto and salmon generate the transcript-level abundances needed for tximport-style imports, allowing you to aggregate estimates for downstream differential expression analysis.

Does RNA-seq quantification support reproducible versioning and parameter documentation?▼

Yes, RNA-seq quantification workflows emphasize reproducibility by maintaining clear versioning and documenting parameters throughout the process of generating gene counts and QC summaries.

What inputs are required to run an alignment-free quantification workflow?▼

Alignment-free quantification requires RNA-seq FASTQ files, a reference transcriptome, and GTF or GFF annotations to output transcript abundances and gene-level counts.

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