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Installation

renalprog is a heavy package. Installation requires about 4.5 GB of disk space and a stable internet connection.

Prerequisites

  • Python 3.9 or higher
  • R 4.0+ (for enrichment analysis) - Can be installed via conda/mamba (recommended)
  • Conda or Mamba (recommended for environment management)
  • CUDA-capable GPU (optional, for faster VAE training)

Quick Setup with environment.yml (Easiest)

# Clone repository
git clone https://github.com/gprolcastelo/renalprog.git
cd renalprog

# Create environment from file (includes Python, R, and all dependencies)
mamba env create -f environment.yml
mamba activate renalprog

# Install the package in editable mode
pip install -e .

Manual Setup

# Clone repository
git clone https://github.com/gprolcastelo/renalprog.git
cd renalprog

# Create environment with Python 3.9 AND R
mamba create -n renalprog "python==3.9" "r-base>=4.0"
mamba activate renalprog

# Install R packages via conda (recommended for reproducibility)
mamba install -c conda-forge r-gprofiler2 r-ggplot2 r-optparse

# Install uv for faster Python package management
pip install uv

# Install Python package
uv pip install -e .

# Install testing dependencies
uv pip install pytest pytest-cov

Note: Installing R via conda/mamba ensures all dependencies are managed in the same environment, improving reproducibility.

Alternative: Using pip + venv

git clone https://github.com/gprolcastelo/renalprog.git
cd renalprog
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -e .

With Development Dependencies

# Using uv
uv pip install -e ".[dev]"

# Or using pip
pip install -e ".[dev]"

R Dependencies for Enrichment Analysis

The package includes R scripts for gene enrichment analysis. You can install R dependencies in several ways:

If using conda/mamba environment:

# Activate your environment
mamba activate renalprog

# Install R and packages (if not done during initial setup)
mamba install -c conda-forge r-base r-gprofiler2 r-ggplot2 r-optparse

Option 2: Via R's install.packages()

If you already have R installed system-wide or prefer CRAN:

# Install R packages using the provided script
Rscript scripts/r_analysis/install_r_packages.R

On Windows PowerShell: 

Rscript scripts\r_analysis\install_r_packages.R

Required R packages: - r-gprofiler2 / gprofiler2 - Gene enrichment via g:Profiler API - r-ggplot2 / ggplot2 - Visualization - r-optparse / optparse - Command-line parsing

GSEA Installation (Required for Step 6)

For dynamic enrichment analysis, you need to install GSEA:

  1. Download from: https://www.gsea-msigdb.org/gsea/index.jsp
  2. Extract to project root (creates GSEA_4.3.2/ directory)
  3. See GSEA Installation Guide for detailed instructions