Join

Plate IV.164 · Publications

Modeling fragment counts improves single-cell ATAC-seq analysis

Article in Nature Methods, 4 December 2023.

Open accessSingle Cell RNA, Gene Expression

  1. Laura D. Martens
  2. David S. Fischer
  3. Vicente A. Yépez
  4. Fabian J. Theis
  5. Julien Gagneur

Abstract

Single-cell ATAC sequencing coverage in regulatory regions is typically binarized as an indicator of open chromatin. Here we show that binarization is an unnecessary step that neither improves goodness of fit, clustering, cell type identification nor batch integration. Fragment counts, but not read counts, should instead be modeled, which preserves quantitative regulatory information. These results have immediate implications for single-cell ATAC sequencing analysis.

Versions2

  1. PublishedNature Methods10.1038/s41592-023-02112-6
  2. PreprintbioRxiv10.1101/2022.05.04.490536

Cite

@article{martens2023modeling,
  title = {{Modeling fragment counts improves single-cell ATAC-seq analysis}},
  author = {Martens, Laura D. and Fischer, David S. and Yépez, Vicente A. and Theis, Fabian J. and Gagneur, Julien},
  journal = {Nature Methods},
  publisher = {Springer Science and Business Media LLC},
  year = {2023},
  month = dec,
  doi = {10.1038/s41592-023-02112-6},
  url = {https://doi.org/10.1038/s41592-023-02112-6},
  pmid = {38049697},
  pmcid = {PMC10776385}
}
.bib file