Datasetpublic

plantcad/PlantCAD2_zero_shot_tasks

🌱 PlantCAD2 Zero-Shot Tasks Zero-shot evaluation tasks for plant genomics using PlantCAD2.This dataset contains tasks designed to evaluate model performance without task-specific training. 📂 Available Tasks 🔬 Cross-species Evolutionary Conservation Task Name Description Samples Metric conservation_within_andropogoneae Predict conserved vs non-conserved sites using alignments within 35 Andropogoneae genomes 19,030 vs 19,030 AUROC… See the full description on the dataset page: https://huggingface.co/datasets/plantcad/PlantCAD2_zero_shot_tasks.

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face

0likes544downloads

Dataset Card

🌱 PlantCAD2 Zero-Shot Tasks

Zero-shot evaluation tasks for plant genomics using PlantCAD2. This dataset contains tasks designed to evaluate model performance without task-specific training.

📂 Available Tasks

🔬 Cross-species Evolutionary Conservation

Task Name	Description	Samples	Metric
`conservation_within_andropogoneae`	Predict conserved vs non-conserved sites using alignments within 35 Andropogoneae genomes	19,030 vs 19,030	AUROC
`conservation_within_poaceae_non_tis`	Predict conserved vs non-conserved coding sites (excluding TIS) within Poaceae	103,368 vs 80,317	AUROC
`conservation_within_poaceae_tis`	Predict conserved vs non-conserved TIS sites	26,650 vs 10,012	AUROC

🧬 Key Junction Recovery

Task Name	Description	Samples	Metric
`tis_recovery`	Recover masked ATG start codon (maize)	39,035	Accuracy
`tts_recovery`	Recover masked TAG/TAA/TGA stop codon (maize)	39,035	Accuracy
`donor_recovery`	Recover masked GT splice donor motif (maize)	153,869	Accuracy
`acceptor_recovery`	Recover masked AG splice acceptor motif (maize)	153,869	Accuracy

🌽 Within-species Conservation (Maize)

Task Name	Description	Samples	Metric
`tis_core_noncore_classification`	Predict core TIS vs non-core TIS	28,291 vs 8,118	AUROC
`tts_core_noncore_classification`	Predict core TTS vs non-core TTS	28,291 vs 8,118	AUROC
`donor_core_noncore_classification`	Predict core splice donor vs non-core splice donor	123,183 vs 21,367	AUROC
`acceptor_core_noncore_classification`	Predict core splice acceptor vs non-core splice acceptor	123,183 vs 21,367	AUROC

🧩 Structural Variant Effect

Task Name	Description	Samples	Metric
`structural_variant_effect_prediction`	Predict conserved deletions vs non-conserved deletions	7,662 vs 10,413	AUPRC

📑 Data Format

Task Type	Fields	Description
Classification	`sequence`	DNA sequence (string)
	`label`	Binary label: `0 = negative`, `1 = positive`
Recovery	`sequence`	DNA sequence (string)

📊 Data Splits

Split	Description
`test`	General test data
`test_maize`	Zea mays (corn)-specific test data
`test_tomato`	Solanum lycopersicum (tomato)-specific test data

🚀 Usage Example

python

from datasets import load_dataset, get_dataset_config_names

# List all available tasks
tasks = get_dataset_config_names("plantcad/PlantCAD2_zero_shot_tasks")
print("Available tasks:", tasks)

# Example: Classification task
classification_data = load_dataset("plantcad/PlantCAD2_zero_shot_tasks", "conservation_within_poaceae_tis")
test_split = classification_data['test']
print(f"Test samples: {len(test_split)}")
print(f"Sample: {test_split[0]}")

# Example: TIS recovery task
recovery_data = load_dataset("plantcad/PlantCAD2_zero_shot_tasks", "tis_recovery")
if 'test_maize' in recovery_data:
    maize_data = recovery_data['test_maize']
    print(f"Maize recovery samples: {len(maize_data)}")