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Upload LOL-EVE eQTL dataset v1.0

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+ ---
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+ language:
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+ - en
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+ license: mit
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+ task_categories:
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+ - text-generation
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+ size_categories:
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+ - 10K<n<100K
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+ configs:
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+ - config_name: default
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+ data_files: "*.parquet"
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+ default: true
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+ ---
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+
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+ # LOL-EVE eQTL Causal Identification Dataset
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+
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+ ## Dataset Description
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+
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+ This dataset contains causal eQTL (expression quantitative trait loci) identification data for evaluating variant effect prediction models. The dataset includes indel variants in promoter regions with associated gene expression data and functional annotations.
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+
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+ ## Dataset Structure
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+
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+ - **Total Variants**: 7,090
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+ - **Species**: Primates (Homo sapiens)
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+ - **Variant Types**: Insertions and deletions in promoter regions
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+ - **Sequence Length**: Up to 1,000bp promoter regions
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+
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+ ## Features
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+
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+ ### Basic Variant Information
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+ - `gene`: Gene symbol
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+ - `species`: Species name
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+ - `clade`: Evolutionary clade
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+ - `chromosome`: Chromosome
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+ - `position`: Genomic position
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+ - `ref`: Reference allele
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+ - `alt`: Alternative allele
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+ - `variant_type`: Type of variant (insertion/deletion/substitution)
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+
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+ ### Sequences
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+ - `wt_sequence`: Wild-type sequence
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+ - `var_sequence`: Variant sequence
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+ - `sequence_length`: Length of sequence
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+ - `wt_sequence_start`: Start position of sequence
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+
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+ ### Labels and Annotations
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+ - `pip`: Posterior inclusion probability (causal label)
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+ - `indel_length`: Length of indel
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+ - `distance_tss`: Distance to transcription start site
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+ - `gsa_depth`: GSA depth
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+ - `depth_category`: Depth category
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+
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+ ### Functional Annotations
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+ - `phylop`: PhyloP conservation score
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+ - `cadd`: CADD score
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+ - `gc_percentage_delta`: GC content change
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+
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+ ## Usage
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ # Load the dataset
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+ dataset = load_dataset("cshearer/LOL-EVE-eQTL")
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+
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+ # Access the data
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+ print(f"Dataset size: {len(dataset['train'])}")
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+ print(f"Features: {dataset['train'].features}")
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+
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+ # Example: Get causal variants (PIP >= 0.01)
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+ causal_variants = dataset['train'].filter(lambda x: x['pip'] >= 0.01)
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+ print(f"Causal variants: {len(causal_variants)}")
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+ ```
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+
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+ ## Citation
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+
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+ If you use this dataset in your research, please cite:
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+
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+ ```bibtex
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+ @article{loleve2024,
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+ title={LOL-EVE: Language of Life - Evolutionary Variant Effects},
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+ author={Your Name and Collaborators},
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+ journal={Nature},
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+ year={2024}
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+ }
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+ ```
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+
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+ ## License
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+
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+ This dataset is released under the MIT License.