metadata
license: mit
This uploaded dataset is a sample data of 12k rows for train and 1.2k for test to get idea of the dataset used in making of PathoPreter
https://huggingface.co/YADAV0206/PathoPreter-4B-SNV-Pathogen-ClinVar-gnomAD
The model's full training dataset contains approximately 144k pathogenic variants and 1.05 million benign variants, for a total of about 1.2 million samples and Testing have 55k total different samples with 11 seperate ablations tests (on same 55k rows) making around 12*55k=660k”
To get the Dataset contact Rohit Yadav
📦 Dataset Availability
Dataset Construction and Availability:
The datasets used to train and evaluate PathoPreter (including large-scale ClinVar-derived SNV corpora, controlled ablation test suites, and robustness evaluation datasets) were fully constructed in-house using publicly available, permissively licensed genomic resources such as ClinVar and gnomAD. All upstream sources are properly credited and explicitly permit commercial use and redistribution.
Significant original engineering and curation effort was applied beyond raw data usage. This included large-scale extraction, normalization, schema unification, quality control, deduplication, and strict train–test disjointness enforcement. Approximately 8 million raw ClinVar variants and ~250 GB of gnomAD VCF data were processed and merged into production-grade Parquet datasets optimized for large-scale analytics, machine learning training, and downstream integration.
The end-to-end data construction process required approximately 150 hours of compute time and over 250 hours of expert engineering and curation work. The resulting datasets constitute a high-value derived data asset, distinct from the original source distributions.
These datasets are available for licensed distribution to startups, enterprises, and research organizations for use in applied genomics, AI/ML model development, benchmarking, variant prioritization workflows, and internal research. Commercial licensing, redistribution terms, and support options are available upon request.
Available components include:(in Parquet and CSV both)
- Large-scale ClinVar-style SNV training dataset
- Held-out test set with identical variants across ablations
- Controlled ablation datasets (signal removal studies)
- Fake-variant's robustness evaluation dataset (see below why is it important in FAKE VARIANT ROBUSTNESS TEST)
- Balanced CSV subsets suitable for classical ML training
- Data audit and leakage-verification scripts
If you are interested in:
- dataset licensing
- research or industry use
- collaboration or benchmarking
- reproducing or extending this work
please contact:
Rohit Yadav
Requests are evaluated on a case-by-case basis.