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--- |
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license: mit |
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tags: |
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- dna |
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- variant-effect-prediction |
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- biology |
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- genomics |
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configs: |
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- config_name: "mendelian_traits" |
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data_files: |
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- split: test |
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path: "mendelian_traits_matched_9/test.parquet" |
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- config_name: "complex_traits" |
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data_files: |
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- split: test |
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path: "complex_traits_matched_9/test.parquet" |
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- config_name: "mendelian_traits_full" |
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data_files: |
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- split: test |
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path: "mendelian_traits_all/test.parquet" |
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- config_name: "complex_traits_full" |
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data_files: |
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- split: test |
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path: "complex_traits_all/test.parquet" |
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--- |
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# 🧬 TraitGym |
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Benchmarking DNA Sequence Models for Causal Regulatory Variant Prediction in Human Genetics |
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🏆 Leaderboard: https://huggingface.co/spaces/songlab/TraitGym-leaderboard |
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## ⚡️ Quick start |
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- Load a dataset |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("songlab/TraitGym", "mendelian_traits", split="test") |
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``` |
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- Example notebook to run variant effect prediction with a gLM, runs in 5 min on Google Colab: `TraitGym.ipynb` [](https://colab.research.google.com/github/songlab-cal/TraitGym/blob/main/TraitGym.ipynb) |
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## 🤗 Resources (https://huggingface.co/datasets/songlab/TraitGym) |
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- Datasets: `{dataset}/test.parquet` |
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- Subsets: `{dataset}/subset/{subset}.parquet` |
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- Features: `{dataset}/features/{features}.parquet` |
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- Predictions: `{dataset}/preds/{subset}/{model}.parquet` |
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- Metrics: `{dataset}/{metric}/{subset}/{model}.csv` |
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`dataset` examples (`load_dataset` config name): |
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- `mendelian_traits_matched_9` (`mendelian_traits`) |
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- `complex_traits_matched_9` (`complex_traits`) |
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- `mendelian_traits_all` (`mendelian_traits_full`) |
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- `complex_traits_all` (`complex_traits_full`) |
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`subset` examples: |
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- `all` (default) |
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- `3_prime_UTR_variant` |
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- `disease` |
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- `BMI` |
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`features` examples: |
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- `GPN-MSA_LLR` |
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- `GPN-MSA_InnerProducts` |
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- `Borzoi_L2` |
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`model` examples: |
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- `GPN-MSA_LLR.minus.score` |
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- `GPN-MSA.LogisticRegression.chrom` |
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- `CADD+GPN-MSA+Borzoi.LogisticRegression.chrom` |
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`metric` examples: |
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- `AUPRC_by_chrom_weighted_average` (main metric) |
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- `AUPRC` |
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## 💻 Code (https://github.com/songlab-cal/TraitGym) |
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- Tries to follow [recommended Snakemake structure](https://snakemake.readthedocs.io/en/stable/snakefiles/deployment.html) |
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- GPN-Promoter code is in [the main GPN repo](https://github.com/songlab-cal/gpn) |
