Scuphr: A probabilistic framework for cell lineage tree reconstruction

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Abstract

Cell lineage tree reconstruction methods are developed for various tasks, such as investigating the development, differentiation, and cancer progression. Single-cell sequencing technologies enable more thorough analysis with higher resolution. We present Scuphr, a distance-based cell lineage tree reconstruction method using bulk and single-cell DNA sequencing data from healthy tissues. Common challenges of single-cell DNA sequencing, such as allelic dropouts and amplification errors, are included in Scuphr. Scuphr computes the distance between cell pairs and reconstructs the lineage tree using the neighbor-joining algorithm. With its embarrassingly parallel design, Scuphr can do faster analysis than the state-of-the-art methods while obtaining better accuracy. The method’s robustness is investigated using various synthetic datasets and a biological dataset of 18 cells.

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Koptagel, H., Jun, S. H., Hård, J., & Lagergren, J. (2024). Scuphr: A probabilistic framework for cell lineage tree reconstruction. PLoS Computational Biology, 20(5 May). https://doi.org/10.1371/journal.pcbi.1012094

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