HuggingFaceBio/clinvar-vep

ClinVar VEP

A ClinVar variant-effect-prediction (VEP) benchmark, for evaluating DNA language models on clinical variant pathogenicity, with two subsets: coding (39,473 variants) and non-coding (15,258 variants).

Each split is a balanced binary classification task: label = 1 for pathogenic / likely pathogenic and label = 0 for benign / likely benign.

Subsets

Config	# variants	benign	pathogenic	Region scope
coding	39,473	17,231	22,242	exonic protein-coding
non_coding	15,258	7,629	7,629	intronic + 5′/3′ UTR

from datasets import load_dataset
coding     = load_dataset("hf-carbon/clinvar-vep-final", "coding",     split="test")
non_coding = load_dataset("hf-carbon/clinvar-vep-final", "non_coding", split="test")

Coding subset — origin

For the coding ClinVar benchmark, we use the ClinVar VEP subset from GenerTeam/variant-effect-prediction, which was originally used in the GPN-MSA study (Benegas et al., 2025). However, wee found that it is largely coding: 39,473 are coding and 1,503 are non-coding. The non-coding subset is also highly label-imbalanced, with 10 pathogenic non-coding variants. We therefore use this dataset as our coding ClinVar benchmark and construct a separate balanced non-coding subset from ClinVar.

Non-coding subset — construction

To construct a separate non-coding ClinVar benchmark, we start from the original ClinVar VCF and restrict to single-nucleotide variants on chromosomes 1–22, X, and Y with binary clinical labels, mapping benign / likely benign to label = 0 and pathogenic / likely pathogenic to label = 1. We retain reviewed variants, annotate each variant using ClinVar consequence terms into broad region classes (coding, non_coding, splice, unknown) and finer subtypes (intronic, utr_5_prime, utr_3_prime, etc.), and then select the clean non-coding subset with coding_status == "non_coding".

This yields a balanced non-coding benchmark of 15,258 variants: 7,629 benign and 7,629 pathogenic, covering intronic (10,310) and UTR variants (4,948 total — 4,174 5′UTR + 774 3′UTR).