Modeling fragment counts improves single-cell ATAC-seq analysis

Laura D. Martens; David S. Fischer; Vicente A. Yépez; Fabian J. Theis; Julien Gagneur

doi:10.1038/s41592-023-02112-6

Modeling fragment counts improves single-cell ATAC-seq analysis

Laura D. Martens, David S. Fischer, Vicente A. Yépez, Fabian J. Theis, Julien Gagneur

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

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.

Original language	English
Pages (from-to)	28-31
Number of pages	4
Journal	Nature Methods
Volume	21
Issue number	1
DOIs	https://doi.org/10.1038/s41592-023-02112-6
State	Published - Jan 2024

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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.",

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AB - 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.

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Modeling fragment counts improves single-cell ATAC-seq analysis

Abstract

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