genetics-viz 0.6.9

A web-based visualization tool for genetics cohort data

Genetics-Viz 🧬

A web-based visualization tool for genetics cohort data, providing interactive analysis and validation of genetic variants.

Features

Core Features

• 📊 Multi-Cohort Management - Browse and analyze multiple cohorts from a single data directory
• 👨‍👩‍👧‍👦 Family Structure Visualization - View pedigree information and family relationships
• 🧬 Variant Analysis - Interactive TanStack-powered tables for DNM (de novo mutations) and WOMBAT analysis
• 🔍 Cohort-Wide Search - Search variants across all samples with filters on locus, genesets, impact, individuals (sex, phenotype, parental status), and validation status
• 📈 Variant Statistics - Interactive charts (chromosome distribution, consequence/validation pie charts) and ideogram visualization with cytoband rendering
• ✅ Variant Validation - Track and validate genetic variants with inheritance patterns
• 🔬 IGV Integration - Built-in IGV.js browser for sequence visualization (CRAM files)
• 🌊 WAVES Validation - Specialized validation workflow for bedGraph/coverage analysis
• 🔐 Authentication & Authorization - YAML-configured user accounts with role-based access (reader, curator, administrator)
• 📂 Multi-Data-Directory - Switch between multiple data directories per user session via YAML config
• 🛠️ Admin Pages - Manage users and data directories from the web interface
• 🎨 Modern UI - Clean, responsive interface built with NiceGUI

Validation Features

• Save validation status (present/absent/uncertain/different/in phase MNV)
• Track inheritance patterns (de novo/paternal/maternal/not paternal/not maternal/either/homozygous)
• Add optional comments to validations
• Mark validations as ignored (excluded from statistics and conflict detection)
• View validation history with timestamps and ignore status
• Interactive validation guide accessible via info button
• Filter variants by validation status
• Automatic conflict detection (ignoring validations marked as ignored)
• Export validation data

Installation

Quick Start with uvx (Recommended)

The easiest way to run genetics-viz without installation:

uvx genetics-viz /path/to/config.yaml

From PyPI

pip install genetics-viz

From Source

# Clone the repository
git clone https://github.com/bourgeron-lab/genetics-viz.git
cd genetics-viz

# Install with uv (recommended)
uv sync
uv run genetics-viz /path/to/config.yaml

# Or install with pip
pip install -e .
genetics-viz /path/to/config.yaml

Alternative: Local Python/Virtualenv

# Create a virtual environment
python3 -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install genetics-viz
pip install genetics-viz

# Run the application
genetics-viz /path/to/config.yaml

Configuration

YAML Config File

The application requires a YAML configuration file listing data directories and users:

data_directories:
  - path: /path/to/data/directory1
    description: "Primary WGS data"
    default: true
  - path: /path/to/data/directory2
    description: "Secondary dataset"

user_list:
  - username: admin
    password: "<sha512-hex-digest>"
    role: administrator
  - username: curator1
    password: "<sha512-hex-digest>"
    role: curator
  - username: viewer
    password: "<sha512-hex-digest>"
    role: reader

# Auto-generated on first run — do not edit manually
storage_secret: "<hex-string>"

Generating Password Hashes

echo -n "your_password" | sha512sum | cut -d' ' -f1

User Roles

Role	Permissions
reader	View all data, cannot save validations or diagnostics
curator	View all data + save validations and diagnostics
administrator	All curator permissions + manage users and data directories

Initial Setup

1. Create a YAML config file with at least one data directory and one administrator user
2. Generate the admin password hash (see above)
3. Run: genetics-viz /path/to/config.yaml
4. Log in with admin credentials at http://localhost:8080/login
5. Use the admin pages to add more users and data directories

Usage

Command Line Options

# Basic usage
genetics-viz /path/to/config.yaml

# With custom host and port
genetics-viz /path/to/config.yaml --host 0.0.0.0 --port 8080

# Full help
genetics-viz --help

Web Interface

Once started, open your browser to http://localhost:8080 (or the specified port). You will be redirected to the login page.

The interface provides:

• Home Page - List of available cohorts
• Cohort View - Family list and overview
• Family View - DNM, WOMBAT, and SV analysis tabs with TanStack tables
• Search Page - Cohort-wide variant search with tabbed filters (Variants and Individuals)
• Variant Statistics - Charts and ideogram views for search results
• Validation Pages - Track variant validations (file-specific and all validations)
• Diagnostic Pages - Track variant diagnostic conclusions
• WAVES Validation - Specialized coverage/bedGraph validation workflow
• Profile Page - View role and change password
• Admin Pages - Manage data directories and users (administrators only)

Data Directory Structure

The tool expects the following directory structure:

data_directory/
├── cohorts/
│   ├── cohort1/
│   │   ├── cohort1.pedigree.tsv
│   │   ├── wombat/
│   │   │   └── cohort1.rare.*.*.results.tsv (cohort-wide search files)
│   │   └── families/
│   │       ├── FAM001/
│   │       │   ├── FAM001.wombat.*.tsv (WOMBAT analysis files)
│   │       │   └── FAM001.dnm.*.tsv (DNM analysis files)
│   │       └── FAM002/
│   │           └── ...
│   └── cohort2/
│       └── ...
├── params/
│   └── genesets/
│       └── *.tsv (gene set files for search filtering)
├── samples/
│   ├── SAMPLE001/
│   │   └── sequences/
│   │       ├── SAMPLE001.GRCh38_GIABv3.cram
│   │       ├── SAMPLE001.GRCh38_GIABv3.cram.crai
│   │       └── SAMPLE001.GRCh38.bedGraph.gz (for WAVES)
│   └── SAMPLE002/
│       └── ...
└── validations/
    ├── snvs.tsv (variant validations)
    └── waves.tsv (WAVES validations)

Required Files

Pedigree File Format

Pedigree files (cohort_name.pedigree.tsv) should be tab-separated. The header is optional - if present, it must start with "FID" (a leading # is stripped automatically):

With header:

#FID	IID	PAT	MAT	SEX	PHENOTYPE
FAM001	SAMPLE001	SAMPLE003	SAMPLE004	1	2
FAM001	SAMPLE002	0	0	2	1

Without header (positional columns):

FAM001	SAMPLE001	SAMPLE003	SAMPLE004	1	2
FAM001	SAMPLE002	0	0	2	1

Missing/unknown values for parent IDs are 0, -9, or empty. These values are also treated as unknown for sex and phenotype when building filter options.

Column Mapping (case-insensitive, # prefix stripped):

Column	Possible Names
Family ID	FID, family_id, familyid, family
Individual ID	IID, individual_id, sample_id, sampleid, sample
Father ID	PAT, father_id, fatherid, father, paternal_id
Mother ID	MAT, mother_id, motherid, mother, maternal_id
Sex	SEX, gender
Phenotype	PHENOTYPE, affected, status, affection

CRAM Files (for IGV visualization)

• Format: SAMPLE_ID.GRCh38_GIABv3.cram
• Index: SAMPLE_ID.GRCh38_GIABv3.cram.crai
• Location: samples/SAMPLE_ID/sequences/

BedGraph Files (for WAVES validation)

• Format: SAMPLE_ID.GRCh38.bedGraph.gz
• Location: samples/SAMPLE_ID/sequences/

Analysis Files

• DNM files: FAMILY_ID.dnm.*.tsv (must contain chr:pos:ref:alt column)
• WOMBAT files: FAMILY_ID.wombat.*.tsv (must contain #CHROM, POS, REF, ALT columns)

GHFC Lab Usage

Prerequisites

You need to either:

• Be on the Institut Pasteur network, OR
• Be connected via VPN

Mounting ghfc_wgs from Helix

On macOS

# Mount the network drive
# In Finder: Go > Connect to Server (⌘K)
# Enter: smb://helix.pasteur.fr/ghfc_wgs
# Or via command line:
open 'smb://helix.pasteur.fr/projects/ghfc_wgs'

The drive will be mounted at /Volumes/ghfc_wgs

On Linux

# Create mount point
sudo mkdir -p /mnt/ghfc_wgs

# Mount via CIFS
sudo mount -t cifs //helix.pasteur.fr/projects/ghfc_wgs /mnt/ghfc_wgs -o username=YOUR_USERNAME,domain=PASTEUR

# Or add to /etc/fstab for automatic mounting:
# //helix.pasteur.fr/projects/ghfc_wgs /mnt/ghfc_wgs cifs username=YOUR_USERNAME,password=YOUR_PASSWORD,domain=PASTEUR,uid=1000,gid=1000 0 0

Running genetics-viz for GHFC Data

Method 1: Using uvx (Recommended - No Installation)

# Install uv if you haven't already
curl -LsSf https://astral.sh/uv/install.sh | sh

# Run directly with uvx
uvx genetics-viz /path/to/genetics_viz.yaml

# On Linux (adjust path):
uvx genetics-viz /path/to/genetics_viz.yaml

Method 2: Using uv with Local Installation

# Install uv
curl -LsSf https://astral.sh/uv/install.sh | sh

# Install genetics-viz
uv pip install genetics-viz

# Run the application
genetics-viz /path/to/genetics_viz.yaml

Access the Application

Once started, open your browser to:

http://localhost:8080

To access from other machines on the network:

genetics-viz /path/to/genetics_viz.yaml --host 0.0.0.0 --port 8080

Then access via: http://YOUR_MACHINE_IP:8080

Validation Workflow

SNV Validation

1. Navigate to a variant table (DNM or WOMBAT tabs, or Validation pages)
2. Click "View in IGV" button for a variant
3. In the dialog:
   • Review variant details with collapsible sections
   • Add additional samples (parents, siblings, or by barcode)
   • Examine CRAM tracks in IGV viewer
   • Click the info button (ℹ️) to view validation guidelines
   • Set validation status (default: present) and inheritance pattern
   • Add an optional comment
   • Click "Save Validation"
4. The validation is saved to validations/snvs.tsv
5. View validation history below the form
   • Toggle the "Ignore" switch to exclude validations from statistics
   • Ignored validations appear with reduced opacity
6. Validation/all page aggregates multiple validations per variant/sample
   • Shows unique list of users who validated each variant
   • Computes final status from non-ignored validations

WAVES Validation

1. Go to "Validation" > "Waves" in the menu
2. Select a cohort and pedigree
3. Select a sample from the pedigree
4. Click "View on IGV" for the sample
5. In the dialog:
   • Review bedGraph coverage tracks for the sample
   • Add additional samples for comparison
   • Set validation status
   • Click "Save Validation"
6. The validation is saved to validations/waves.tsv

Development

# Clone repository
git clone https://github.com/bourgeron-lab/genetics-viz.git
cd genetics-viz

# Install with development dependencies
uv sync --dev

# Run tests
uv run pytest

# Run linter
uv run ruff check .

# Format code
uv run ruff format .

# Run with auto-reload for development
uv run genetics-viz --reload /path/to/config.yaml

Validation File Formats

SNV Validations (validations/snvs.tsv)

Version 0.2.0+ format:

FID Variant Sample User Inheritance Validation Comment Ignore Timestamp
FAM001 chr1:12345:A:T SAMPLE001 username de novo present Initial validation 0 2026-01-18T10:30:00
FAM001 chr1:12345:A:T SAMPLE001 reviewer homozygous present Confirmed 0 2026-01-19T14:20:00
FAM002 chr2:67890:G:C SAMPLE002 username unknown uncertain Low coverage 1 2026-01-18T11:00:00

Columns:

• FID: Family ID
• Variant: chr:pos:ref:alt format
• Sample: Sample ID
• User: Username who performed validation
• Inheritance: de novo, paternal, maternal, not paternal, not maternal, either, homozygous, or unknown
• Validation: present, absent, uncertain, different, or "in phase MNV"
• Comment: Optional free-text comment
• Ignore: 0 (included) or 1 (excluded from statistics and conflict detection)
• Timestamp: ISO format timestamp

Migration from v0.1.1:

If upgrading from v0.1.1, use the provided migration script:

./utils/snvs_validations_migration_0.1.1_to_0.2.0.sh /path/to/data/validations/snvs.tsv

This adds the Comment and Ignore columns with default values.

WAVES Validations (validations/waves.tsv)

Cohort Pedigree Sample User Validation Timestamp
cohort1 FAM001 SAMPLE001 username present 2026-01-18T10:30:00

Troubleshooting

Cannot access GHFC data

• Verify VPN connection or Pasteur network access
• Check that ghfc_wgs is properly mounted
• Verify mount path (/Volumes/ghfc_wgs on macOS, /mnt/ghfc_wgs on Linux)

IGV not displaying

• Ensure CRAM files and indices (.crai) exist
• Check that files follow naming convention: SAMPLE_ID.GRCh38_GIABv3.cram
• Verify IGV.js is loading (check browser console)

Pedigree file not recognized

• Ensure tab-separated format
• Verify required columns are present
• Check file naming: cohort_name.pedigree.tsv

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

For detailed changes between versions, see CHANGELOG.md.

License

MIT License - See LICENSE file for details

Citation

If you use this tool in your research, please cite:

Genetics-Viz: A web-based visualization tool for genetics cohort data
GitHub: https://github.com/bourgeron-lab/genetics-viz

Support

For issues, questions, or feature requests, please open an issue on GitHub: https://github.com/bourgeron-lab/genetics-viz/issues