datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
greengenes
Greengenes Dataset (modified for deeptaxa)
This dataset contains 16S rRNA gene sequences with hierarchical taxonomic annotations, designed for training and evaluating models like DeepTaxa. It is a processed version of the Greengenes database, widely used in microbiome research.
Dataset Details
The dataset includes the following files:
File Name
Type
Number of Sequences
Size
gg_2024_09_training.fna.gz
FASTA (sequences)
277,336
~96.4 MB… See the full description on the dataset page: https://huggingface.co/datasets/systems-genomics-lab/greengenes.applied-genomicscontext-population-generalization-genomics-v01
Dataset
ClarusC64/context-population-generalization-genomics-v01
This dataset tests one capability.
Can a model keep genetic claims inside the population and context they were measured in.
Core rule
Genomic findings are population bound.
A claim must respect
ancestry
cohort design
sample context
transfer limits
What is true in one populationdoes not automatically hold in another.
Canonical labels
WITHIN_SCOPE
OUT_OF_SCOPE
Files… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/context-population-generalization-genomics-v01.africa-synth-cancer-cancer-genomics-molecular-africa-all
Cancer Genomics Molecular Africa | Africa (Electric Sheep Africa metadata inventory)
Size category: 1K<n<10K - Formats: csv - Sector: health - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Health datasets help… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-cancer-cancer-genomics-molecular-africa-all.uncertainty-incompleteness-functional-unknowns-genomics-v01
Dataset
ClarusC64/uncertainty-incompleteness-functional-unknowns-genomics-v01
This dataset tests one capability.
Can a model resist inventing biological function when evidence is incomplete.
Core rule
Genomics contains large unknowns.
A claim must respect
incomplete annotation
context specific regulation
limits of prediction
absence of functional validation
Prediction is not proof.
Annotation is not mechanism.
Expression is not causation.
Canonical labels… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/uncertainty-incompleteness-functional-unknowns-genomics-v01.causal-inference-variant-interpretation-genomics-v01
Dataset
ClarusC64/causal-inference-variant-interpretation-genomics-v01
This dataset tests one capability.
Can a model distinguish association from causation when interpreting genetic variants.
Core rule
Genomic evidence has tiers.
A claim must respect
evidence strength
effect size
penetrance
inheritance logic
Association does not equal causation.
Risk does not equal destiny.
Uncertain does not equal pathogenic.
Canonical labels
WITHIN_SCOPE… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/causal-inference-variant-interpretation-genomics-v01.