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Single-cell 3D genome reconstruction in the haploid setting using rigidity theory

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Single-cell 3D genome reconstruction in the haploid setting using rigidity theory. / Dewar, Sean; Grasegger, Georg; Kubjas, Kaie et al.
In: Journal of Mathematical Biology, Vol. 90, No. 4, 45, 01.04.2025.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Dewar, S, Grasegger, G, Kubjas, K, Mohammadi, F & Nixon, A 2025, 'Single-cell 3D genome reconstruction in the haploid setting using rigidity theory', Journal of Mathematical Biology, vol. 90, no. 4, 45. https://doi.org/10.1007/s00285-025-02203-2

APA

Dewar, S., Grasegger, G., Kubjas, K., Mohammadi, F., & Nixon, A. (2025). Single-cell 3D genome reconstruction in the haploid setting using rigidity theory. Journal of Mathematical Biology, 90(4), Article 45. https://doi.org/10.1007/s00285-025-02203-2

Vancouver

Dewar S, Grasegger G, Kubjas K, Mohammadi F, Nixon A. Single-cell 3D genome reconstruction in the haploid setting using rigidity theory. Journal of Mathematical Biology. 2025 Apr 1;90(4):45. Epub 2025 Mar 29. doi: 10.1007/s00285-025-02203-2

Author

Dewar, Sean ; Grasegger, Georg ; Kubjas, Kaie et al. / Single-cell 3D genome reconstruction in the haploid setting using rigidity theory. In: Journal of Mathematical Biology. 2025 ; Vol. 90, No. 4.

Bibtex

@article{22b0dcba7ae64ed7921f32997d837d64,
title = "Single-cell 3D genome reconstruction in the haploid setting using rigidity theory",
abstract = "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.",
keywords = "Hi-C, 3D genome reconstruction, 92E10, Semidefinite programming, 52C25, Rigidity",
author = "Sean Dewar and Georg Grasegger and Kaie Kubjas and Fatemeh Mohammadi and Anthony Nixon",
year = "2025",
month = apr,
day = "1",
doi = "10.1007/s00285-025-02203-2",
language = "English",
volume = "90",
journal = "Journal of Mathematical Biology",
issn = "0303-6812",
publisher = "Springer Verlag",
number = "4",

}

RIS

TY - JOUR

T1 - Single-cell 3D genome reconstruction in the haploid setting using rigidity theory

AU - Dewar, Sean

AU - Grasegger, Georg

AU - Kubjas, Kaie

AU - Mohammadi, Fatemeh

AU - Nixon, Anthony

PY - 2025/4/1

Y1 - 2025/4/1

N2 - 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.

AB - 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.

KW - Hi-C

KW - 3D genome reconstruction

KW - 92E10

KW - Semidefinite programming

KW - 52C25

KW - Rigidity

U2 - 10.1007/s00285-025-02203-2

DO - 10.1007/s00285-025-02203-2

M3 - Journal article

VL - 90

JO - Journal of Mathematical Biology

JF - Journal of Mathematical Biology

SN - 0303-6812

IS - 4

M1 - 45

ER -