Dewar Sean, Grasegger Georg, Kubjas Kaie, Mohammadi Fatemeh, Nixon Anthony
School of Mathematics, University of Bristol, Bristol, UK.
Johann Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences, Linz, Austria.
J Math Biol. 2025 Mar 29;90(4):45. doi: 10.1007/s00285-025-02203-2.
This article considers the problem of 3-dimensional genome reconstruction for single-cell data, and the uniqueness of such reconstructions in the setting of haploid organisms. We consider multiple graph models as representations of this problem, and use techniques from graph rigidity theory to determine identifiability. Biologically, our models come from Hi-C data, microscopy data, and combinations thereof. Mathematically, we use unit ball and sphere packing models, as well as models consisting of distance and inequality constraints. In each setting, we describe and/or derive new results on realisability and uniqueness. We then propose a 3D reconstruction method based on semidefinite programming and apply it to synthetic and real data sets using our models.
本文考虑了单细胞数据的三维基因组重建问题,以及在单倍体生物背景下此类重建的唯一性。我们将多种图模型视为该问题的表示形式,并使用图刚性理论中的技术来确定可识别性。从生物学角度来看,我们的模型来自Hi-C数据、显微镜数据及其组合。在数学上,我们使用单位球和球堆积模型,以及由距离和不等式约束组成的模型。在每种情况下,我们都描述和/或推导了关于可实现性和唯一性的新结果。然后,我们提出了一种基于半定规划的三维重建方法,并将其应用于使用我们模型的合成数据集和真实数据集。