environment.yml

name: elife-delay-splice
channels:
  - nvidia
  - bioconda
  - conda-forge
  - defaults
dependencies:
  - python=3.11
  - bedtools>=2.30
  - pip
  - pip:
    # Deep learning
    # Pin to the stack known to work on this cluster's NVIDIA driver line.
    # Newer torch wheels can pull CUDA 13 builds that require newer drivers.
    - torch==2.6.0
    - pytorch-lightning==2.4.0

    # Custom fork of tfmodisco-lite with reverse complementation optional (for use with gReLU)
    - git+https://github.com/jsdearbo/tfmodisco-lite.git@main

    # gReLU genomics library (includes Borzoi model loading and attribution)
    # Custom fork with pre-computed attribution functionality for TF-MoDISco
    - git+https://github.com/jsdearbo/gReLU.git@pre-computed-attr-modisco

    # Fine-tuning experiment tracking
    - wandb

    # Bioinformatics I/O
    - h5py>=3.10
    - pysam>=0.22
    - pyBigWig>=0.3
    - genomepy>=0.15

    # Data science
    - numpy>=1.24,<2.0
    - pandas>=2.0
    - scipy>=1.10
    - scikit-learn>=1.3

    # Visualisation
    - matplotlib>=3.7
    - seaborn>=0.13
    - logomaker>=0.8
    - adjustText>=1.0

    # Motif scanning (FIMO); gReLU requires tangermeme>=0.5.0
    - tangermeme>=0.5.0

    # Utilities
    - pyyaml>=6.0
    - tqdm