Modeling fragment counts improves single-cell ATAC-seq analysis

Martens, L. D.; Fischer, D. S.; Theis, F. J.; Gagneur, J.

doi:10.1101/2022.05.04.490536

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bioRxiv · 10.1101/2022.05.04.490536

Modeling fragment counts improves single-cell ATAC-seq analysis

Martens, L. D.·Fischer, D. S.·Theis, F. J.·Gagneur, J.

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Abstract

Single-cell ATAC-sequencing (scATAC-seq) coverage in regulatory regions is typically binarized as an indicator of open chromatin. However, the implications of scATAC-seq data binarization have not systematically been assessed. Here, we show that the goodness-of-fit of existing models and their applications, including clustering, cell type identification, and batch integration, are improved by a quantitative treatment of the fragment counts. These results have immediate implications for scATAC-seq analysis.

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Martens, L. D., Fischer, D. S., Theis, F. J., Gagneur, J.. 2022-05-04. Modeling fragment counts improves single-cell ATAC-seq analysis. https://doi.org/10.1101/2022.05.04.490536

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