TraitGym + 8,192 bp pre-extracted windows

This dataset is a repackaging of songlab/TraitGym (Benegas, Eraslan & Song, bioRxiv 2025.02.11.637758), with one extra step: for every variant we pre-extract the 8,192 bp window centered on the variant from the hg38 reference, plus the same window with the alt allele substituted.

The variants, labels and matched controls are identical to the original songlab/TraitGym _matched_9 configs.

Configs

• mendelian_traits (n = 3,380): 338 putative-causal non-coding variants from 113 monogenic Mendelian diseases (curated from OMIM), matched 9:1 against gnomAD common-variant controls on chromosome × consequence × TSS-distance.
• complex_traits (n = 11,400): 1,140 putative-causal non-coding variants from 83 polygenic UK BioBank traits (PIP > 0.9 from statistical fine-mapping), matched 9:1 against PIP < 0.01 controls on chromosome × consequence × TSS-distance × MAF × LD score.

Schema

column	description
chrom	chromosome (1–22, X, Y)
pos	1-indexed hg38 position
ref, alt	single bases (SNVs only)
label	int 0/1 (1 = causal/positive, 0 = matched control)
class	"LOF" (label=1) or "FUNC/INT" (label=0) — added so the standard brca_eval.py AUROC code path works without changes
consequence	molecular consequence from the source dataset
tss_dist	distance to nearest TSS
match_group	matched-controls group ID (preserve from source)
score	continuous PIP for complex_traits; None for mendelian_traits
ref_seq, var_seq	8,192 bp window centered on the variant (variant at index 4096), forward strand from chr-fasta-hg38 (UCSC). var_seq is ref_seq with the alt base substituted at index 4096. Reverse-complement is computed at eval time when --rev_comp_avg is requested (matches TraitGym's run_vep_evo2.py strand-symmetric scoring).

Eval methodology

Same recipe as our other VEP evals (BRCA1, BRCA2, ClinVar): delta = LL(var_seq) − LL(ref_seq) from a centered 8,192 bp window. Score per-variant; AUROC / AUPRC / AUPRC_by_chrom_weighted_average (the TraitGym leaderboard convention) against the binary label. Optional --rev_comp_avg averages the LLR computed on the forward window and on its reverse-complement, exactly as TraitGym does.

Eval scripts:

• reproduction-evo2-evals/brca/brca_eval.py — gene-agnostic centered+full-LL eval
• Sharded variant: reproduction-evo2-evals/traitgym/ — array-job sharding for Evo2 7B+/40B

Citation

If you use TraitGym, cite the original paper:

@article{benegas2025traitgym,
  title  = {Benchmarking DNA Sequence Models for Causal Regulatory Variant Prediction in Human Genetics},
  author = {Benegas, Gonzalo and Eraslan, Gokcen and Song, Yun S.},
  journal = {bioRxiv},
  year   = {2025},
  doi    = {10.1101/2025.02.11.637758}
}

Leaderboard: songlab/TraitGym-leaderboard on HF Spaces.