bio-liquid-biopsy-pipeline

Tumor fraction estimation from shallow WGS cfDNA data is performed using ichorCNA, which analyzes copy number alterations to quantify the tumor-derived fraction in plasma samples. The pipeline orchestrates this alongside preprocessing and fragment QC.

Somatic mutation detection in targeted cfDNA panels is handled by calling variants from deep sequencing data and applying CHIP filtering to remove clonal hematopoiesis artifacts. This ensures high-confidence somatic VAFs for downstream tracking.

Longitudinal tracking of ctDNA dynamics is supported by analyzing serial liquid biopsy samples to monitor tumor fraction and mutation burden trends over time. This allows researchers to assess treatment response through serial plasma collections.

UMI-aware deduplication for cfDNA preprocessing is executed during the initial workflow stage by collapsing reads with unique molecular identifiers to reduce collateral sequencing errors. This prepares high-quality input for both tumor fraction estimation and mutation detection.

cfDNA fragment size analysis is included as a QC and profiling step to verify cfDNA quality and detect characteristic mono- and di-nucleosome patterns. Optional fragmentomics features provide additional fragment-level insights.

To run an end-to-end cfDNA liquid biopsy pipeline, invoke the workflow with a sample configuration specifying bam_file, data_type, reference, bed_file, and output_dir. The pipeline then orchestrates preprocessing, tumor fraction estimation, mutation detection, and longitudinal analysis automatically.