kreview 0.0.10

Evaluate cfDNA fragmentomics features for ctDNA detection

kreview

Advanced cfDNA Fragmentomics Core Evaluation Engine

---

🧬 Overview

kreview is a production-grade, notebook-first (nbdev) evaluation engine designed for high-throughput cancer liquid biopsy fragmentomics feature analysis. Developed at Memorial Sloan Kettering (MSKCC), it processes cohorts containing tens of thousands of samples using an embedded DuckDB query engine with chunked I/O and automatic retry logic.

📖 Full Documentation

🚀 Features

• 5-Tier ctDNA Taxonomy: MSK-IMPACT paired-inference to label True ctDNA+, Possible ctDNA+, Possible ctDNA−, Healthy Normal, and Insufficient Data.
• DuckDB Dynamic Data Lake: In-memory read_parquet bindings with chunked I/O and exponential backoff retry. Builds a merged SQL-queryable kreview_lake.duckdb on demand.
• Multi-Model Evaluation: Random Forest, XGBoost, and Logistic Regression with Stratified K-Fold CV, SHAP explainability, and subgroup analysis.
• Interactive Dashboards: Plotly-native HTML reports with ROC curves, violin plots, SHAP beeswarm/waterfall, and per-cancer-type sensitivity tables.
• 26 Built-In Evaluators: Modular extractors covering fragment sizes (FSC, FSD, FSR), nucleosome protection (WPS, TFBS), cleavage motifs (EndMotif, BreakPointMotif), chromatin accessibility (ATAC), motif divergence (MDS), and orientation (OCF).

⚙️ Quick Start

Installation

[!IMPORTANT] Quarto is strictly required for programmatic dashboard generation. Because quarto-cli wrapper packages are unreliable across Python environments, kreview assumes the Quarto executable is installed dynamically on your OS or container.

Option 1: Docker (Recommended "Batteries-Included" Method)

The easiest way to run kreview without managing external dependencies is to use our pre-built Docker container (hosted on GHCR). It natively ships with Python 3.12, all ML libraries, and the underlying quarto linux binaries configured flawlessly:

docker pull ghcr.io/msk-access/kreview:latest
docker run -v /your/data:/data ghcr.io/msk-access/kreview:latest \
  kreview run --cancer-samplesheet /data/cancer.csv ...

Option 2: Local Install (Pip)

If you install via pip, you must separately install Quarto via your OS manager:

1. Install Quarto: Follow the official Quarto Installation Guide (e.g. brew install quarto on macOS).
2. Install kreview:

git clone https://github.com/msk-access/kreview.git
cd kreview
pip install -e .

Running the Pipeline

PYTHONUNBUFFERED=1 kreview run \
  --cancer-samplesheet "/path/to/cancer/samplesheet.csv" \
  --healthy-xs1-samplesheet "/path/to/healthy/xs1/samplesheet.csv" \
  --healthy-xs2-samplesheet "/path/to/healthy/xs2/samplesheet.csv" \
  --cbioportal-dir "/path/to/cBioPortal_MAF_CNA_SV/" \
  --krewlyzer-dir "/path/to/unified_krewlyzer_results" \
  --output output/ \
  --workers 4 \
  --export-duckdb

Dashboard Access

Once finished, open the generated HTML reports:

open output/reports/ATAC_dashboard.html

🏗️ nbdev Architecture

This project operates as an nbdev repo. Do not edit .py scripts manually in kreview/. Build natively inside Jupyter notebooks within nbs/ and trigger:

nbdev-export

📚 Resources

• Documentation — Full user and developer guide
• Contributing — How to contribute
• Changelog — Version history