README.md

---
configs:
  - config_name: reference
    data_files:
      - split: train
        path: reference/train.parquet
      - split: valid
        path: reference/valid.parquet
      - split: test
        path: reference/test.parquet
  - config_name: personalized
    data_files:
      - split: train
        path: personalized/train.parquet
      - split: valid
        path: personalized/valid.parquet
      - split: test
        path: personalized/test.parquet
license: cc-by-4.0
task_categories:
  - tabular-regression
tags:
  - biology
  - genomics
  - dna-methylation
  - epigenetics
  - sequence-to-function
  - collaborative-cross
  - mouse
size_categories:
  - 10M<n<100M
---

# S2F Mouse Methylation Dataset

Sequence-to-function dataset for predicting CpG DNA methylation from genomic sequence in nine genetically diverse Collaborative Cross mouse founder strains.

## Dataset Description

This dataset contains approximately 20 million sequence-methylation examples derived from reduced representation bisulfite sequencing (RRBS) data from nine Collaborative Cross founder strains. Each example pairs a 2,000-nucleotide DNA sequence window centered at a CpG dinucleotide with the corresponding methylation proportion (averaged across three biological replicates per strain).

Two encoding configurations are provided:

- **`reference`**: All strains use the mm10 reference genome sequence, producing identical input sequences regardless of strain identity.
- **`personalized`**: Strain-specific genetic variants are incorporated using [g2gtools](https://github.com/churchill-lab/g2gtools) and IUPAC ambiguity codes. For example, a heterozygous A/T SNP is represented by IUPAC symbol `W` and encoded as `[0.5, 0, 0, 0.5]`.

## Usage

```python
from datasets import load_dataset

# Load reference encoding
ds = load_dataset("cbreenmachine/s2f-mouse-methylation", "reference", split="train")

# Load personalized encoding
ds = load_dataset("cbreenmachine/s2f-mouse-methylation", "personalized", split="train")
```

## Column Descriptions

| Column | Type | Description |
|--------|------|-------------|
| `feature` | string | 2,000-nucleotide DNA sequence centered at a CpG site. Reference config uses standard nucleotides (A, C, G, T, N). Personalized config additionally uses IUPAC ambiguity codes (M, R, W, S, K, Y, B, D, H, V) to represent strain-specific variants. |
| `methylation` | float | Mean methylation proportion across three biological replicates (range 0--1). |
| `subject` | string | Mouse strain identifier: 129S1_SvImJ, A_J, C57BL_6, CAST_EiJ, DBA_2J, NOD_ShiLtJ, NZO_HlLtJ, PWK_PhJ, or WSB_EiJ. |
| `chrom` | string | Chromosome number (1--19). |
| `name` | string | Locus identifier in mm10 reference coordinates, enabling cross-strain comparisons at the same genomic position. |

## Data Splits

| Split | Chromosomes | Purpose |
|-------|-------------|---------|
| `train` | 1--12 | Model training |
| `valid` | 14 | Validation / early stopping |
| `test` | 15--19 | Held-out evaluation |

All nine strains are represented in every split.

## Mouse Strains

Nine Collaborative Cross founder strains spanning three *Mus musculus* subspecies:

| Strain | Subspecies | Notes |
|--------|-----------|-------|
| C57BL/6J | *M. m. domesticus* | Reference strain (mm10 genome) |
| 129S1/SvImJ | *M. m. domesticus* | |
| A/J | *M. m. domesticus* | |
| DBA/2J | *M. m. domesticus* | |
| NOD/ShiLtJ | *M. m. domesticus* | |
| NZO/HlLtJ | *M. m. domesticus* | |
| CAST/EiJ | *M. m. castaneus* | Wild-derived |
| PWK/PhJ | *M. m. musculus* | Wild-derived |
| WSB/EiJ | *M. m. domesticus* | Wild-derived |

## Source Data

- **Methylation data**: Tyler et al. (2023). Reduced representation bisulfite sequencing of hepatocyte DNA from 12-week-old female mice. Three biological replicates per strain, averaged.
- **Genetic variants**: Svenson et al. (2012). SNPs and indels for Collaborative Cross founder strains.
- **Reference genome**: GRCm38/mm10.

## Associated Paper

> Breen C, Keles S. Variant-Aware Sequence Encoding Does Not Improve Deep Learning Prediction of DNA Methylation in Genetically Diverse Mice. (2026).

## Citation

```bibtex
@article{breen2026variant,
  title={Variant-Aware Sequence Encoding Does Not Improve Deep Learning Prediction of DNA Methylation in Genetically Diverse Mice},
  author={Breen, Coleman and Kele{\c{s}}, S{\"u}nd{\"u}z},
  year={2026}
}
```

## License

CC-BY-4.0

## Repository Structure

```
s2f-mouse-methylation/
├── README.md
├── reference/
│   ├── train.parquet
│   ├── valid.parquet
│   └── test.parquet
└── personalized/
    ├── train.parquet
    ├── valid.parquet
    └── test.parquet
```

## Uploading the Data

The parquet files are located on the training server at:
```
/storage10/cebreen/S2M-data-v3/data_derived/mouse/s2m_input/reference_merged/{train,valid,test}.parquet
/storage10/cebreen/S2M-data-v3/data_derived/mouse/s2m_input/personal_merged/{train,valid,test}.parquet
```

To populate this repo:

```bash
# Create directory structure
mkdir -p reference personalized

# Copy from server (adjust hostname as needed)
scp server:/storage10/cebreen/S2M-data-v3/data_derived/mouse/s2m_input/reference_merged/{train,valid,test}.parquet reference/
scp server:/storage10/cebreen/S2M-data-v3/data_derived/mouse/s2m_input/personal_merged/{train,valid,test}.parquet personalized/

# Initialize as HuggingFace dataset repo
huggingface-cli repo create s2f-mouse-methylation --type dataset
git init
git remote add origin https://huggingface.co/datasets/cbreenmachine/s2f-mouse-methylation
git lfs install
git lfs track "*.parquet"
git add .gitattributes README.md reference/ personalized/
git commit -m "Initial upload: reference and personalized encodings"
git push -u origin main
```

Note: Files >10MB are automatically handled by Git LFS on HuggingFace.