Datasets:
metadata
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
data.csv: The main dataset stored in comma-separated tabular format.1_data.ipynb: Jupyter notebook containing the preprocessing steps used to generate the.csvfile.
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
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)