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). 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.
适合你,如果手头有bulk RNA-seq数据,需要完整的差异表达分析流程。
npx oh-my-skill add k-dense-ai/scientific-agent-skills/bulk-rnaseqcurl -fsSL https://oh-my-skill.com/install.sh | bash -s -- k-dense-ai/scientific-agent-skills/bulk-rnaseqnpx oh-my-skill verify k-dense-ai/scientific-agent-skills/bulk-rnaseq怎么用
商店整理自技能原文 · 版本 3f825ca · 表述以原文为准Claude 会引导你完成批量RNA-seq分析:从原始FASTQ文件开始,经过质量控制和修剪,比对和定量,构建基因计数矩阵,然后进行差异表达分析、通路富集,并生成发表级图表。
当你提到“分析我的RNA-seq”、“从FASTQ到DESeq2”、“运行nf-core/rnaseq”、“STAR/Salmon定量”等关键词,或要求进行完整的批量RNA-seq差异表达分析时触发。