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--- |
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license: mit |
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task_categories: |
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- tabular-classification |
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tags: |
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- biology |
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- genomics |
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pretty_name: "ChromHMM fullstack annotation of the human genome" |
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size_categories: |
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- 1M<n<10M |
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--- |
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# human-chromhmm-fullstack |
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## Dataset Summary |
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This dataset provides a multi-class annotation of genomic regions across the hg38 genome. It is derived from the ChromHMM fullstack annotation (Vu & Ernst, 2022; https://doi.org/10.1186/s13059-021-02572-z). Genomic regions are classified into 16 states. The data is derived from https://public.hoffman2.idre.ucla.edu/ernst/2K9RS//full_stack/full_stack_annotation_public_release/hg38/hg38_genome_100_segments.bed.gz. |
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## Repository Content |
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1. `data.csv`: The main dataset stored in comma-separated tabular format. |
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2. `1_data.ipynb`: Jupyter notebook containing the preprocessing steps used to generate the `.csv` file. |
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## Dataset Structure |
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| Column | Type | Description | |
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| :--- | :--- | :--- | |
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| chrom | string | Chromosome name (e.g., chr1) | |
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| start | int | Start coordinate of the genomic interval | |
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| end | int | End coordinate of the genomic interval | |
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| state | string | Chromatin state annotation (e.g., EnhWk, Quies) | |
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| interval_idx | int | Unique numerical index for the specific genomic interval | |
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| enformer_split | string | Overlap with the data splits used for training the Enformer model | |
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| split | string |Splits used for downstream modeling (training/validation/test) | |
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## Usage |
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```python |
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import pandas as pd |
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from huggingface_hub import hf_hub_download |
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file_path = hf_hub_download( |
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repo_id="Genentech/human-chromhmm-fullstack-data", |
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filename="data.csv" |
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) |
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df = pd.read_csv(file_path) |
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``` |
