Bulk rnaseq
End-to-end bulk RNA-seq orchestrator — takes raw FASTQ reads through QC and trimming (FastQC, fastp/Trim Galore), alignment and quantification (STAR, Salmon, featureCounts), assembles a gene-level counts matrix, then hands off to differential expression (pydeseq2), pathway/GSEA enrichment (pathway-enrichment), and publication figures (scientific-visualization).
What it does
End-to-end bulk RNA-seq orchestrator — takes raw FASTQ reads through QC and trimming (FastQC, fastp/Trim Galore), alignment and quantification (STAR, Salmon, featureCounts), assembles a gene-level counts matrix, then hands off to differential expression (pydeseq2), pathway/GSEA enrichment (pathway-enrichment), and publication figures (scientific-visualization).
This is a reusable SKILL.md workflow from K-Dense. It gives an AI agent task-specific instructions to follow when you ask for this kind of work. The source page contains the full workflow, requirements, and any supporting files.
How to try it
- Read the original skill.
Check that the workflow fits your task, and review any tools, accounts, or permissions it needs.
- Follow the publisher’s setup guide.
Installation depends on your agent. Use the source repository’s instructions and include any required supporting files.
- Give your agent a concrete task.
Describe your goal and provide the relevant inputs. Try a small, reversible example and review the result.
The explanation is based on the publisher’s skill metadata. The source file was retrieved on 25 Sep 2026; we have not executed or independently validated the skill. Agent compatibility and any paid service requirements should be checked upstream.