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featurecounts-rna-counting

Count aligned RNA-seq reads overlapping gene features in GTF annotations.

298|27|Updated Feb 18, 2026
Search Tags:#bioinformatics#genomics#differential expression#rna-seq#featurecounts#read counting
One-click install
npx skills add https://github.com/jaechang-hits/SciAgent-Skills --skill featurecounts-rna-counting
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: featurecounts-rna-counting
Source: https://github.com/jaechang-hits/SciAgent-Skills/tree/main/skills/genomics-bioinformatics/featurecounts-rna-counting
Command: npx skills add https://github.com/jaechang-hits/SciAgent-Skills --skill featurecounts-rna-counting

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires subread, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the process of counting RNA sequencing reads that overlap with specific genomic features, such as genes, from aligned sequencing data.

Core Features & Use Cases

  • Gene-level Quantification: Generates a count matrix essential for differential gene expression analysis.
  • Multi-sample Processing: Efficiently handles multiple BAM files in a single run.
  • Strandedness Handling: Correctly accounts for library preparation protocols (unstranded, stranded, reverse-stranded).
  • Use Case: After aligning RNA-seq reads to a reference genome, use this Skill to count how many reads map to each gene across all your experimental samples, preparing the data for tools like DESeq2 or edgeR.

Quick Start

Run featureCounts to count RNA-seq reads from multiple BAM files using the provided GTF annotation file and save the output to 'gene_counts.txt'.

Frequently Asked Questions about featurecounts-rna-counting

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

FAQPage Schema
How do I count RNA-seq reads per gene from sorted BAM files?▼

To count RNA-seq reads per gene, this Skill processes sorted BAM files against a GTF annotation file to generate a gene-level count matrix. It automates read overlapping with genomic features for multiple samples in a single batch run.

Can I process multiple BAM files for differential expression analysis at once?▼

Yes, you can process multiple BAM files for differential expression analysis simultaneously. The Skill efficiently handles multi-sample batch processing and outputs a unified gene count matrix suitable for downstream tools like DESeq2 or edgeR.

How does featureCounts handle library strandedness during read counting?▼

featureCounts handles library strandedness by correctly accounting for different preparation protocols during read counting. It supports unstranded, stranded, and reverse-stranded libraries to ensure reads are accurately assigned to overlapping gene features.

Do I need the Subread package to generate a gene-level count matrix from GTF annotations?▼

Yes, you need the Subread package installed to generate a gene-level count matrix from GTF annotations. The Skill relies on Subread's featureCounts functionality to execute the read overlapping and quantification process.

What is the best way to prepare aligned RNA-seq data for DESeq2 or edgeR?▼

The best way to prepare aligned RNA-seq data for DESeq2 or edgeR is to generate a gene-level count matrix. This Skill quantifies reads overlapping gene features in a GTF file and outputs the exact matrix format required by these differential expression analysis tools.

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