Complete cell-free DNA analysis workflow from plasma sequencing to clinical interpretation. Supports both shallow WGS for tumor fraction estimation and targeted panels for mutation detection.
# cfDNA preprocessing
conda install -c bioconda fgbio bwa samtools
# Tumor fraction (sWGS)
# R: devtools::install_github('GavinHaLab/ichorCNA')
# Mutation detection (panel)
conda install -c bioconda vardict-java
# Fragmentomics
pip install finaletoolkit pysam pandas numpy matplotlibTell your AI agent what you want to do:
- "Analyze my plasma cfDNA sequencing data"
- "Estimate tumor fraction from shallow WGS"
- "Detect ctDNA mutations from my targeted panel"
- "Run a complete liquid biopsy pipeline"
"I have plasma cfDNA from a targeted panel with UMIs. Run a complete analysis."
"Set up a liquid biopsy pipeline for my sWGS samples."
"Preprocess my cfDNA BAM with UMI consensus calling."
"Run ichorCNA to estimate tumor fraction from my 0.5x sWGS."
"Detect mutations at 0.5% VAF and filter out CHIP variants."
"Track ctDNA levels across my serial samples."
- Check pre-analytical quality factors
- Preprocess with UMI-aware deduplication
- Verify cfDNA quality (fragment size distribution)
- Estimate tumor fraction (sWGS) OR detect mutations (panel)
- Filter CHIP variants
- Optionally analyze fragmentomics
- Track longitudinal dynamics if serial samples
- sWGS (0.1-1x) is for tumor fraction; panels are for mutations
- ichorCNA detects >= 3% tumor fraction reliably
- VarDict detects >= 0.5% VAF with UMI consensus
- Always filter CHIP genes (DNMT3A, TET2, ASXL1, etc.)
- Pre-analytical factors matter: use Streck tubes or process EDTA quickly
- FinaleToolkit replicates DELFI patterns (DELFI is commercial, not software)
- liquid-biopsy/cfdna-preprocessing - Preprocessing details
- liquid-biopsy/tumor-fraction-estimation - ichorCNA analysis
- liquid-biopsy/ctdna-mutation-detection - Variant calling
- liquid-biopsy/fragment-analysis - Fragmentomics
- liquid-biopsy/longitudinal-monitoring - Serial tracking