variant-effect
variant-effect-prediction
Updates
[2025-09-09] We have added ClinVar variant effect prediction results to the repository. The evaluation dataset was sourced from SongLab. The benchmark includes comparisons of GENERator against Evo2, NT, NT-v2, HyenaDNA, GPN-MSA, CADD, phyloP, and phastCons.
Abouts
The human reference genome data is sourced from the NCBI website.
We have applied minor formatting adjustments to the dataset to facilitate streamlined data analysis.
How to use
from datasets… See the full description on the dataset page: https://huggingface.co/datasets/GenerTeam/variant-effect-prediction.variant_effect_coding
🧬 BioReasonIncentivizing Multimodal Biological Reasoning within a DNA-LLM Model
Variant Effect Coding Dataset
50,083 core variant entries from GPN-MSA study using ClinVar pathogenic variants and gnomAD benign variants (MAF>5%), split by chromosome (Chr 1-7,9-22,X,Y for train, Chr 8 for test) for pathogenic/benign classification.
Usage
from datasets import load_dataset
dataset = load_dataset("wanglab/variant_effect_coding")
example = dataset["train"][0]… See the full description on the dataset page: https://huggingface.co/datasets/wanglab/variant_effect_coding.cagi-variant-effect-glm-tang
GLM-Tang Task 3: CAGI Regulatory Variant Effects
This dataset packages the saturation-mutagenesis MPRA variants used for
Task 3 of Tang et al. The task is zero-shot variant-effect prediction:
compare a reference sequence with a matched single-nucleotide alternate
sequence and test whether the model score tracks the measured regulatory
effect.
Choosing a configuration
Config
Rows
Sequence length
Intended use
paper-230
5,056
230 nt
Official… See the full description on the dataset page: https://huggingface.co/datasets/Taykhoom/cagi-variant-effect-glm-tang.variant_effect_non_snv
🧬 BioReasonIncentivizing Multimodal Biological Reasoning within a DNA-LLM Model
Variant Effect Coding Non-SNVs Dataset
36,088 core non-SNV entries from ClinVar 2024-02-28 release, filtered for coding variants with ≥2-star review status, using stratified train/test splits for balanced disease representation in pathogenic/benign classification.
Usage
from datasets import load_dataset
dataset = load_dataset("wanglab/variant_effect_non_snv")
example =… See the full description on the dataset page: https://huggingface.co/datasets/wanglab/variant_effect_non_snv.demo_variant_effect_pathogenic_clinvar_256Martyn_VariantEffects_GAMEModule Version: martyn_variant_effects_20260610-163836_EDT
GAME Schema Version: v 1.0
Github Link: https://github.com/de-Boer-Lab/GAME-Martyn-variant-effects-evaluator
Additional information can be found on GitHub: Genomic API for Model Evaluation
Original publication can be found here: Martyn et al., 2025