bio-liquid-biopsy-pipeline
Cell-free DNA analysis pipeline from plasma sequencing to tumor monitoring. Preprocesses cfDNA reads, analyzes fragment patterns, estimates tumor fraction from sWGS, and optionally detects mutations from targeted panels. Use when analyzing liquid biopsy samples for cancer detection or monitoring.
npx skills add majiayu000/claude-skill-registry --skill liquid-biopsy-pipeline --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.
# Liquid Biopsy Analysis Pipeline Complete workflow for cfDNA analysis from sequencing to clinical interpretation. ## Pipeline Overview ``` Pre-analytical QC → cfDNA Preprocessing → Fragment QC ↓ ┌─────────────────┴─────────────────┐ ↓ ↓ sWGS Branch Panel Branch ↓ ↓ ichorCNA VarDict/smCounter2 (Tumor Fraction) (Mutation Detection) ↓ ↓ └─────────────────┬─────────────────┘ ↓ Longitudinal Tracking ``` ## Step 0: Pre-Analytical QC ```python def check_preanalytical_quality(sample_metadata): ''' Pre-analytical factors critical for cfDNA quality. Requirements: - Streck tube: up to 7 days at room temperature - EDTA tube: process within 6 hours - Avoid hemolysis - Store extracted DNA at -80C ''' issues = [] if sample_metadata['tube_type'] == 'EDTA': if sample_metadata['processing_delay_hours'] > 6: issues.append('EDTA tube processed > 6 hours - risk of gDNA contamination') if sample_metadata['hemolysis_score'] > 1: issues.append('Hemolysis detected - expect cellular DNA contamination') return issues ``` ## Step 1: cfDNA Preprocessing with UMI Consensus ```bash # For UMI-tagged libraries (targeted panels) # fgbio pipeline # Extract UMIs fgbio ExtractUmisFromBam \ --input raw.bam \ --output
- Pipeline Overview
- Step 0: Pre-Analytical QC
- Step 1: cfDNA Preprocessing with UMI Consensus
- Step 2: Fragment QC Checkpoint
- Step 3a: Tumor Fraction Estimation (sWGS)
- Step 3b: Mutation Detection (Targeted Panel)
- Step 4: CHIP Filtering
- Step 5: Fragmentomics Analysis (Optional)
- Step 6: Longitudinal Tracking
- Complete Pipeline Script
- Related Skills
For UMI-tagged libraries (targeted panels) fgbio pipeline Extract UMIs fgbio ExtractUmisFromBam \ Align bwa mem -t 8 -Y reference.fa with_umis.bam | \ samtools view -bS - > aligned.bam Group by UMI fgbio GroupReadsByUmi \ Consensus calling
What does the bio-liquid-biopsy-pipeline skill do?
Cell-free DNA analysis pipeline from plasma sequencing to tumor monitoring. Preprocesses cfDNA reads, analyzes fragment patterns, estimates tumor fraction from sWGS, and optionally detects mutations from targeted panels. Use when analyzing liquid biopsy samples for cancer detection or monitoring.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill liquid-biopsy-pipeline --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.