README.md

---
license: mit
task_categories:
- tabular-classification
tags:
- biology
- genomics
pretty_name: "ChromHMM fullstack annotation of the human genome"
size_categories:
- 1M<n<10M
---

# human-chromhmm-fullstack

## Dataset Summary
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.

## Repository Content
1. `data.csv`: The main dataset stored in comma-separated tabular format.
2. `1_data.ipynb`: Jupyter notebook containing the preprocessing steps used to generate the `.csv` file.

## Dataset Structure

| Column | Type | Description |
| :--- | :--- | :--- |
| chrom | string | Chromosome name (e.g., chr1) |
| start | int | Start coordinate of the genomic interval |
| end | int | End coordinate of the genomic interval |
| state | string | Chromatin state annotation (e.g., EnhWk, Quies) |
| interval_idx | int | Unique numerical index for the specific genomic interval |
| enformer_split | string | Overlap with the data splits used for training the Enformer model |
| split | string |Splits used for downstream modeling (training/validation/test) |

## Usage

```python
import pandas as pd
from huggingface_hub import hf_hub_download

file_path = hf_hub_download(
    repo_id="Genentech/human-chromhmm-fullstack-data", 
    filename="data.csv"
)

df = pd.read_csv(file_path)
```