bulk-fastq-quantification

Converts bulk RNA-seq FASTQ or SRA inputs into gene-level count matrices.

13|2|Updated Apr 5, 2026
One-click install
npx skills add https://github.com/omicverse/omicverse-skills --skill bulk-fastq-quantification
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bulk-fastq-quantification
Source: https://github.com/omicverse/omicverse-skills/tree/main/src/omicverse_skills/skills/bulk-fastq-quantification
Command: npx skills add https://github.com/omicverse/omicverse-skills --skill bulk-fastq-quantification

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill removes the manual friction of bulk RNA-seq preprocessing by turning raw FASTQ or SRA inputs into gene-level count matrices ready for differential expression analysis.

Core Features & Use Cases

  • SRA download and FASTQ preparation: Fetch runs, validate downloads, convert to FASTQ, and handle single-end or paired-end layouts.
  • Quality control and quantification: Run fastp for cleanup, then choose either STAR plus featureCounts for alignment-based counting or kb-python BULK for faster alignment-free quantification.
  • DESeq2 handoff: Assemble raw integer counts into a matrix that plugs directly into ov.bulk.pyDEG for downstream DE analysis and volcano plots.
  • Use case: A researcher with four bulk RNA-seq samples can ask this Skill to download or load reads, quantify expression, and return a clean count matrix for immediate statistical testing.

Quick Start

Give this Skill your bulk RNA-seq FASTQ files or SRR accessions and ask it to perform QC, quantification, and count-matrix assembly for DESeq2.

Frequently Asked Questions about bulk-fastq-quantification

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

FAQPage Schema
How do I convert bulk RNA-seq FASTQ files into a count matrix for DESeq2?▼

To convert bulk RNA-seq FASTQ files into a count matrix for DESeq2, this Skill runs fastp QC followed by STAR plus featureCounts or kb-python BULK alignment-free quantification, outputting raw integer counts.

Can I download SRA runs and prepare them for bulk RNA-seq quantification automatically?▼

Yes, you can download SRA runs and prepare them for bulk RNA-seq quantification automatically. This Skill fetches SRR accessions, validates downloads, converts them to FASTQ, and handles paired-end or single-end layouts.

What is the best way to quantify bulk RNA-seq reads without genome alignment?▼

The best way to quantify bulk RNA-seq reads without genome alignment is using kb-python BULK, which provides faster alignment-free quantification directly from FASTQ inputs into gene-level count matrices.

Does this bulk RNA-seq preprocessing workflow support both paired-end and single-end reads?▼

Yes, this bulk RNA-seq preprocessing workflow supports both paired-end and single-end reads. It automatically resolves read layouts during FASTQ preparation and applies the appropriate quantification parameters.

How does the STAR plus featureCounts workflow generate raw integer counts for differential expression?▼

The STAR plus featureCounts workflow generates raw integer counts by aligning FASTQ reads to a reference genome with STAR, then summarizing gene-level features with featureCounts into a DESeq2-ready matrix.

Do I need to manually build genome references before running STAR or kb-python quantification?▼

No, you do not need to manually build genome references before running STAR or kb-python quantification. This Skill requires automatic tool resolution and reference building during the FASTQ to counts pipeline.