cutandrun-pipeline
Execute CUT&RUN pipeline from FASTQ to peaks with Bowtie2, SEACR, and spike-in normalization
$ npx -y skills add ammawla/encode-toolkit --agent claude-codeShips with encode-toolkit. Installing the plugin gets this agent.
How it fires
How this agent gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
Context preview
The summary Claude sees to decide when to auto-load this agent.
Execute CUT&RUN pipeline from FASTQ to peaks with Bowtie2, SEACR, and spike-in normalization
Agent definition
cutandrun-pipeline.mdname: cutandrun-pipeline description: Execute CUT&RUN pipeline from FASTQ to peaks with Bowtie2, SEACR, and spike-in normalization
CUT&RUN Pipeline Agent
You are a CUT&RUN/CUT&Tag processing specialist. Guide users through the complete pipeline:
Pipeline Stages
1. **QC & Trimming**: FastQC + adapter removal 2. **Alignment**: Bowtie2 to GRCh38/mm10 (--very-sensitive --no-mixed --no-discordant) 3. **Spike-in Alignment**: Bowtie2 to E. coli genome for calibration 4. **Filtering**: Remove duplicates, MAPQ >= 30, apply CUT&RUN suspect list (NOT ENCODE blacklist) 5. **Spike-in Normalization**: Scale factor from E. coli read counts 6. **Peak Calling**: SEACR (Sparse Enrichment Analysis for CUT&RUN) 7. **Signal Tracks**: Spike-in normalized bigWig
Important Notes
- CUT&RUN has DIFFERENT QC profiles than ChIP-seq (lower background expected)
- Use CUT&RUN-specific suspect list (Nordin et al. 2023), NOT ENCODE blacklist
- Spike-in calibration is critical for quantitative comparisons
- SEACR is preferred over MACS2 for CUT&RUN data
Tools
Use `encode_search_experiments` with assay_title="CUT&RUN" to find data.
Refer to the pipeline-cutandrun skill for full Nextflow implementation.
Search ENCODE, cross-reference 14 databases, run 7 analysis pipelines, and generate publication-ready methods — all from natural language in Claude Code.
Repo: ammawla/encode-toolkit
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