Agent skill · Data & Analytics

bio-clip-seq-clip-preprocessing

Preprocess CLIP-seq data including adapter trimming, UMI extraction, and PCR duplicate removal. Use when preparing raw CLIP, iCLIP, or eCLIP reads for peak calling.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill clip-preprocessing --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 3 KB
Bundled scripts: none
Path: skills/analysis/clip-preprocessing/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# CLIP-seq Preprocessing ## UMI Extraction (eCLIP/iCLIP) ```bash # Extract UMI from read 1 umi_tools extract \ --stdin=reads_R1.fastq.gz \ --read2-in=reads_R2.fastq.gz \ --bc-pattern=NNNNNNNNNN \ --stdout=R1_umi.fastq.gz \ --read2-out=R2_umi.fastq.gz # bc-pattern: UMI barcode pattern # N = UMI base # For eCLIP: typically 10-nt UMI in read 1 ``` ## Adapter Trimming ```bash # Trim adapters after UMI extraction cutadapt \ -a AGATCGGAAGAGCACACGTCT \ -A AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT \ -m 18 \ -o trimmed_R1.fastq.gz \ -p trimmed_R2.fastq.gz \ R1_umi.fastq.gz R2_umi.fastq.gz ``` ## Two-Pass Trimming (eCLIP) ```bash # eCLIP protocol has inline adapters # First pass: trim 3' adapter cutadapt -a AGATCGGAAGAGC -m 18 -o pass1.fq.gz input.fq.gz # Second pass: trim 5' adapter (read-through) cutadapt -g AGATCGGAAGAGC -m 18 -o pass2.fq.gz pass1.fq.gz ``` ## PCR Duplicate Removal ```bash # After alignment, deduplicate using UMIs umi_tools dedup \ --stdin=aligned.bam \ --stdout=deduped.bam \ --paired \ --method=unique # Methods: # unique: Exact UMI match # cluster: Allow UMI mismatches (default) # adjacency: Network-based clustering ``` ## Python Preprocessing ```python from umi_tools import UMI

What's inside
Steps it walks through
  1. UMI Extraction (eCLIP/iCLIP)
  2. Adapter Trimming
  3. Two-Pass Trimming (eCLIP)
  4. PCR Duplicate Removal
  5. Python Preprocessing
  6. Quality Control
  7. Related Skills
Ships with 1 file
  • metadata.json
Commands it runs
Extract UMI from read 1
umi_tools extract \
N = UMI base
For eCLIP: typically 10-nt UMI in read 1
Trim adapters after UMI extraction
cutadapt \
R1_umi.fastq.gz R2_umi.fastq.gz
eCLIP protocol has inline adapters
First pass: trim 3' adapter
cutadapt -a AGATCGGAAGAGC -m 18 -o pass1.fq.gz input.fq.gz
More from claude-skill-registry
All skills →
About this skill
What does the bio-clip-seq-clip-preprocessing skill do?

Preprocess CLIP-seq data including adapter trimming, UMI extraction, and PCR duplicate removal. Use when preparing raw CLIP, iCLIP, or eCLIP reads for peak calling.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill clip-preprocessing --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.

Keep going