bio-workflows-clip-pipeline
End-to-end CLIP-seq analysis from FASTQ to binding sites and motif enrichment. Use when analyzing protein-RNA interactions from CLIP-based methods.
npx skills add majiayu000/claude-skill-registry --skill clip-pipeline-gptomics-bioskills-6e420f37 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# CLIP-seq Pipeline ## Pipeline Overview ``` FASTQ → QC → UMI extract → Trim adapters → Align → Filter → Dedup → Peak call → Annotate → Motifs ``` ## CLIP Method Variants | Method | UMI | Crosslink Site | Adapter | |--------|-----|----------------|---------| | HITS-CLIP | Optional | Deletions | 3' adapter | | PAR-CLIP | Optional | T→C mutations | 3' adapter | | iCLIP | Required | 5' of read | 3' adapter | | eCLIP | Required | 5' of read | 3' adapter | ## Step 1: Quality Control ```bash # Initial QC fastqc reads.fastq.gz -o qc_pre/ # Check for adapter contamination and UMI structure # For eCLIP: expect 10nt UMI at read start zcat reads.fastq.gz | head -n 100 | cut -c1-15 ``` ## Step 2: UMI Extraction ```bash # eCLIP (10nt UMI at 5' end) umi_tools extract \ --stdin=reads.fastq.gz \ --bc-pattern=NNNNNNNNNN \ --stdout=extracted.fastq.gz \ --log=umi_extract.log # iCLIP (5nt experimental barcode + 5nt UMI) umi_tools extract \ --stdin=reads.fastq.gz \ --bc-pattern=NNNNNXXXXX \ --stdout=extracted.fastq.gz ``` ## Step 3: Adapter Trimming ```bash # Trim 3' adapter (common eCLIP adapter) cutadapt -a AGATCGGAAGAGCACACGTCTGAACTCCAGTCA \ --minimum-length 20 \ --quality-cutoff 20 \ -o trimmed.fas
- Pipeline Overview
- CLIP Method Variants
- Step 1: Quality Control
- Step 2: UMI Extraction
- Step 3: Adapter Trimming
- Step 4: Alignment
- Step 5: Alignment Filtering
- Step 6: PCR Deduplication
- Step 7: Peak Calling
- Step 8: Peak Annotation
- Step 9: Motif Analysis
- Step 10: Cross-link Site Analysis
- Quality Checkpoints
- Complete Pipeline Script
Initial QC fastqc reads.fastq.gz -o qc_pre/ Check for adapter contamination and UMI structure For eCLIP: expect 10nt UMI at read start zcat reads.fastq.gz | head -n 100 | cut -c1-15 eCLIP (10nt UMI at 5' end) umi_tools extract \ iCLIP (5nt experimental barcode + 5nt UMI) Trim 3' adapter (common eCLIP adapter) cutadapt -a AGATCGGAAGAGCACACGTCTGAACTCCAGTCA \
What does the bio-workflows-clip-pipeline skill do?
End-to-end CLIP-seq analysis from FASTQ to binding sites and motif enrichment. Use when analyzing protein-RNA interactions from CLIP-based methods.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill clip-pipeline-gptomics-bioskills-6e420f37 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.