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Bolero data
Data behind Bolero, a sequence-to-function model that predicts cell-state-specific chromatin accessibility and gene expression from DNA sequence: the Bolero-10M single-cell ATAC/RNA collection, the inputs the released models need, and the evaluation sets used in the paper. Raw fragment files are not included.
Layout
| Folder | Contents |
|---|---|
metadata/ |
Cell, sample and cluster metadata per dataset |
metacell/ |
Metacell AnnData and 32 bp parquet stores (training corpus) |
pseudobulk/ |
Pseudobulk records used as model inputs |
reference_bigwig/ |
Reference coverage bigwigs |
peaks/, peak_adata/, gene_adata/ |
Peak sets and peak / gene count matrices |
gene_data/ |
Pseudobulk gene expression and highly variable genes |
cell_embedding/, chromvar/, motif_scan/ |
Cell embeddings, chromVAR scores, JASPAR motif hits |
score_data/ |
Motif score inputs for the +AP1 models |
qtl/ |
caQTL / eQTL evaluation sets |
diff_analysis/ |
Differential accessibility tables |
reference_gtf/ |
Gene annotations |
index/ |
Key-to-path lookup tables used by bolerodata |
Usage
Address files by name through bolerodata,
which downloads each file on first use:
pip install bolerodata
from bolerodata import DATASETS, metadata
metadata.DATASET_METADATA.head() # list datasets (offline)
DATASETS["HumanBrainDev"].cell_metadata # downloads and returns a DataFrame
Model checkpoints live in
arcinstitute/bolero-models.
Citation
Liu H, Mao S, Gallent T, Chen Y, Yan Z, Vogel I, Traunmuller L, Zhang R, Buenrostro JD, Zhou J, Greenberg ME. Predicting cell-state-specific gene regulation from DNA across species. bioRxiv (2026). doi:10.64898/2026.10.19.760026
@article{liu2026bolero,
title = {Predicting cell-state-specific gene regulation from DNA across species},
author = {Liu, H. and Mao, S. and Gallent, T. and Chen, Y. and Yan, Z. and
Vogel, I. and Traunmuller, L. and Zhang, R. and Buenrostro, J. D. and
Zhou, J. and Greenberg, M. E.},
journal = {bioRxiv},
year = {2026},
doi = {10.64898/2026.10.19.760026}
}
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