Denoising single-cell ATAC-seq data with Shannon entropy

Abstract

Single-cell Assay for Transposase Accessible Chromatin with sequencing (scATAC-seq) is widely used to investigate chromatin accessibility but experiments often contain empty droplets, droplets containing damaged nuclei or cellular-debris. Accurately filtering high-quality nuclei is important as noisy droplets contribute reads that can distort downstream analysis and obscure rare cell population. Current approaches often rely on read depth and or predefined genomic features that are not exactly the same as chromatin accessibility landscape. Here, we present a Shannon entropy-based method that filters high-quality nuclei more robustly by quantifying genome-wide accessibility complexity. This approach improves signal-to-noise ratio, increases sensitivity for accessible-region detection, and enables more reliable downstream inference in scATAC-seq studies.

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BibTeX RIS

BibTeX

@misc{yang2026denoising,
  title = {{Denoising single-cell ATAC-seq data with Shannon entropy}},
  author = {Shiyi Yang and Kevin An and Juliana J. Lee and Jase Gehring and Sina Booeshaghi and Haiyan Huang and Aaron Streets},
  howpublished = {bioRxiv},
  year = {2026},
  month = oct,
  doi = {10.64898/2026.10.20.760589},
  url = {https://www.biorxiv.org/content/10.64898/2026.10.20.760589v1},
  note = {CC BY},
}

RIS

TY  - UNPB
TI  - Denoising single-cell ATAC-seq data with Shannon entropy
AU  - Shiyi Yang
AU  - Kevin An
AU  - Juliana J. Lee
AU  - Jase Gehring
AU  - Sina Booeshaghi
AU  - Haiyan Huang
AU  - Aaron Streets
PY  - 2026
DA  - 2026/10/20
PB  - bioRxiv
DO  - 10.64898/2026.10.20.760589
UR  - https://www.biorxiv.org/content/10.64898/2026.10.20.760589v1
AB  - Single-cell Assay for Transposase Accessible Chromatin with sequencing (scATAC-seq) is widely used to investigate chromatin accessibility but experiments often contain empty droplets, droplets containing damaged nuclei or cellular-debris. Accurately filtering high-quality nuclei is important as noisy droplets contribute reads that can distort downstream analysis and obscure rare cell population. Current approaches often rely on read depth and or predefined genomic features that are not exactly the same as chromatin accessibility landscape. Here, we present a Shannon entropy-based method that filters high-quality nuclei more robustly by quantifying genome-wide accessibility complexity. This approach improves signal-to-noise ratio, increases sensitivity for accessible-region detection, and enables more reliable downstream inference in scATAC-seq studies.
SN  - 2692-8205
ER  -

Abstract

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