bulk-rnaseq
自动串联多步工具，显著节省配置与重复性操作时间。
需要大量本地计算资源并安装多种第三方生信软件。
从原始 FASTQ 到差异表达与富集分析的端到端 RNA-seq 编排器。
从原始 FASTQ 一路跑到差异表达与通路富集分析的端到端编排器，包含质控（FastQC、fastp/Trim Galore）、比对/定量（STAR、Salmon、featureCounts）、生成基因计数矩阵，再交给 pydeseq2 做差异分析和 GSEA、绘制发表级图表。有测序数据或想把 reads 做成 DESeq2 输入、通路分析或发表图时用。它把现有工具串成可复现的流水线，补齐 raw→counts 的关键环节。
▸ 展开 SKILL.md 英文原文
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). Use whenever the user has bulk RNA-seq reads or quant output and wants a complete, reproducible differential-expression workflow — e.g. "analyze my RNA-seq", "FASTQ to DESeq2", "run nf-core/rnaseq", "STAR/Salmon quantification", "build a counts matrix for DESeq2", or "go from reads to differentially expressed genes and enriched pathways". Routes between an nf-core/rnaseq (Nextflow) path and a standalone STAR/Salmon path, and covers experimental design, strandedness, and QC gates. For single-cell RNA-seq use the scanpy skill instead.
帮我安装这个 skill：https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/main/skills/bulk-rnaseq/SKILL.mdcurl -fsSL "https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/main/skills/bulk-rnaseq/SKILL.md"# Bulk RNA-seq ## Overview This skill orchestrates a complete, **defensible** bulk RNA-seq differential-expression study, from raw sequencing reads to enriched pathways and figures. It is a router, not a reimplementation: most stages already have dedicated skills in this repo, and this skill connects them in the right order, fills the one real gap (raw reads → a gene-level counts matrix), and enforces the design and QC decisions that determine whether the final result is trustworthy. "Defensible" means three things, applied throughout: - **Reproducible** — pinned pipeline/tool versions, containers where possible, recorded parameters, fixed random seeds. - **Quality-gated** — QC is inspect