Datasets:
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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-data
## 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 chromatin 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
- **Rows:** 5,809,104
- **Columns:** 7
### Data Splits
| Split | Count |
|-------|-------|
| train | 5,042,325 |
| valid | 364,387 |
| test | 402,392 |
### Chromatin States (16 classes)
| State | Count |
|-------|-------|
| Quies | 1,485,576 |
| Acet | 639,669 |
| EnhA | 613,794 |
| ReprPC | 610,147 |
| Tx | 561,526 |
| EnhWk | 543,113 |
| HET | 521,161 |
| TxWk | 254,518 |
| TxEnh | 190,465 |
| TxEx | 121,833 |
| PromF | 88,429 |
| GapArtf | 51,474 |
| BivProm | 48,242 |
| znf | 34,146 |
| TSS | 24,402 |
| DNase | 20,609 |
### Column Descriptions
| 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 (16 classes) |
| 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 (train/valid/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",
repo_type="dataset"
)
df = pd.read_csv(file_path)
```
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