Setup

Setup

Environment

conda env create -f environment.yml && conda activate epinformer_repro

Key dependencies: torch, h5py, pyfaidx, kipoiseq, pyranges, macs2, hicstraw, pyBigWig, scipy, scikit-learn, pandas.

Reference data

bash scripts/download_abc_reference.sh data/reference/hg38     # ABC reference (gene bounds, chrom sizes)

• Genome — supply hg38.fa at data/reference/hg38/hg38.fa (not downloaded by any script).
• Expression labels + Xpresso features + 12-fold CV split — Zenodo 13232430 (expression_data.zip), unzip into data/:
  • GM12878_K562_18377_gene_expr_fromXpresso_with_sequence_strand.csv
  • leave_chrom_out_crossvalidation_split_18377genes.csv

See Datasets and Accessions for the full ENCODE list.

Pretrained checkpoints (optional)

To skip encoder training, download the pretrained enhancer encoders from Hugging Face: JiecongLin/EPInformer-pipeline.

from huggingface_hub import hf_hub_download
ckpt = hf_hub_download("JiecongLin/EPInformer-pipeline", "enhancer_encoders/K562/fold_8.pt")