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SKILL
bulk-rnaseq
Primary machine endpoint
https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/bulk-rnaseqSUMMARY
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.