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Welcome to Krewlyzer

Krewlyzer logo

Krewlyzer is a robust, user-friendly command-line toolkit for extracting a wide range of biological features from cell-free DNA (cfDNA) sequencing data. It is designed for cancer genomics, liquid biopsy research, and clinical bioinformatics, providing high-performance, reproducible feature extraction from BAM files.

Krewlyzer draws inspiration from cfDNAFE and implements state-of-the-art methods for fragmentation, motif, and methylation analysis, all in a modern Pythonic interface with rich parallelization and logging.

TL;DR

Krewlyzer extracts fragmentomics features from cfDNA sequencing data:

  1. Input: BAM file (aligned reads from blood sample)
  2. Output: Tables of numerical features for ML/statistical analysis
  3. Use case: Cancer detection, treatment monitoring, tissue-of-origin

One command does it all: 

krewlyzer run-all -i sample.bam --reference hg19.fa --output results/

New to cfDNA? Start with What is Cell-Free DNA?
Visual learner? See the Overview PDF
Need terminology help? See the Glossary

Key Features

  • Motif Analysis: End motifs, breakpoint motifs, and diversity scores.
  • Fragment Size Analysis: Coverage (FSC), Ratios (FSR), and Distributions (FSD).
  • Nucleosome Positioning: Windowed Protection Scores (WPS).
  • Tissue of Origin: Orientation-aware Fragmentation (OCF).
  • Methylation: Fragment-level methylation patterns (UXM).
  • Mutant Analysis: Mutant vs. Wild-type fragment size comparison (mFSD).

System Requirements

  • Linux or macOS (tested on Ubuntu 20.04, macOS 12+)
  • Python 3.8+
  • ≥16GB RAM recommended for large BAM files
  • Docker (optional, for easiest setup)

Installation

docker pull ghcr.io/msk-access/krewlyzer:0.8.0
# Example usage:
docker run --rm -v $PWD:/data ghcr.io/msk-access/krewlyzer:0.8.0 run-all -i /data/sample.bam --reference /data/hg19.fa --output /data/output_dir

With uv / pip

uv venv .venv
source .venv/bin/activate
uv pip install krewlyzer
Or install from source: 
git clone https://github.com/msk-access/krewlyzer.git
cd krewlyzer
uv pip install .