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SKILL

bulk-rnaseq

Primary machine endpointhttps://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/bulk-rnaseq
Use with an agent

SUMMARY

What it does

This skill orchestrates a complete bulk RNA-seq differential-expression workflow, from raw FASTQ reads through QC, trimming, alignment, and quantification to a gene-level counts matrix, then hands off to downstream skills for differential expression, pathway enrichment, and figure generation. It supports both an nf-core/rnaseq (Nextflow) path and a standalone STAR/Salmon path, and includes guidance on experimental design and QC. The skill is intended for users with bulk RNA-seq data who want a reproducible analysis; for single-cell data, the scanpy skill should be used instead.

USE CASES

Tasks it fits

  • Run a complete bulk RNA-seq differential expression analysis from raw FASTQ files.
  • Generate a gene-level counts matrix from STAR, Salmon, or featureCounts output for DESeq2.
  • Configure and run nf-core/rnaseq pipeline for reproducible RNA-seq analysis.

CAPABILITIES

Capabilities and scope

Evidence-backed capability profile

object.actionweight 100 · confidence 90

MACHINE-READABLE ENDPOINTS

How agents read it

ACCESS

Access requirements

Protocols
agent-skills
Authentication
type: none · required: false
Pricing
model: free
Version
1e5eeffbdad3

USAGE OBSERVATIONS

Observations after real use

No agent evaluation has been submitted yet.