2025_Pillar_VarChAMP

This repository contains the code and data to reproduce Figure 7 from the VarChAMP Pillar project publication.

Paper: A Scalable Variant Effect Mapping Resource for Accelerating Comprehensive Genome Interpretation

Repository Structure

2025_Pillar_VarChAMP/
├── 1_allele_collection/           # Allele processing from Zenodo data
├── 2_dms_bms_overlap_analyses/    # F9 imaging analysis and figures
├── 3_integrated_assay_analyses/   # Cross-assay integration figures
├── utils/                         # Shared utilities
└── env.yml                        # Conda environment

Quick Start

1. Set up environment

conda env create -f env.yml
conda activate varchamp

2. Run analyses

F9 Imaging Figures:

cd 2_dms_bms_overlap_analyses/imaging/2_analyses/F9_analyses/
jupyter notebook 1_F9_visualizations.ipynb
jupyter notebook 2_F9_cell_crops.ipynb

Integrated Assay Figures:

cd 3_integrated_assay_analyses/2_analyses/
jupyter notebook 0_integrative_assay_summary.ipynb

Output Figures

All manuscript figures are saved as SVG files in 3_outputs/pillar_manuscript_figures/ within each analysis directory.

External Resources

Resource	Description
VarChAMP Snakemake Pipeline	Cell Painting image processing pipeline (run batches 7, 8, 11, 12, 13, 14, 15, 16 to reproduce from raw images)
2025_laval_submitted	Source of integrated assay results (will be public with paper release)

License

See LICENSE for details.