datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.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.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.demo_variant_effect_pathogenic_clinvar_256missense-variant-effects
Genetic Variant Pathogenicity Dataset
Dataset Description
This dataset contains annotated genetic variants (mutations) designed for tabular binary classification tasks. The objective is to predict whether a given genetic variant is Pathogenic (disease-causing) or Benign (harmless) based on a rich set of bioinformatics annotations, evolutionary conservation scores, and functional prediction tools.
Task: Binary Classification
Target Column: Pathologic/Benign… See the full description on the dataset page: https://huggingface.co/datasets/bedylmz/missense-variant-effects.demo_variant_effect_causal_eqtl_256demo_variant_effect_pathogenic_omim_256