3D Genome Reconstruction from Partially Phased Hi-C Data

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3D Genome Reconstruction from Partially Phased Hi-C Data. / Cifuentes, Diego; Draisma, Jan; Henriksson, Oskar; Korchmaros, Annachiara; Kubjas, Kaie.

I: Bulletin of Mathematical Biology, Bind 86, Nr. 4, 33, 2024, s. 1.30.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Cifuentes, D, Draisma, J, Henriksson, O, Korchmaros, A & Kubjas, K 2024, '3D Genome Reconstruction from Partially Phased Hi-C Data', Bulletin of Mathematical Biology, bind 86, nr. 4, 33, s. 1.30. https://doi.org/10.1007/s11538-024-01263-7

APA

Cifuentes, D., Draisma, J., Henriksson, O., Korchmaros, A., & Kubjas, K. (2024). 3D Genome Reconstruction from Partially Phased Hi-C Data. Bulletin of Mathematical Biology, 86(4), 1.30. [33]. https://doi.org/10.1007/s11538-024-01263-7

Vancouver

Cifuentes D, Draisma J, Henriksson O, Korchmaros A, Kubjas K. 3D Genome Reconstruction from Partially Phased Hi-C Data. Bulletin of Mathematical Biology. 2024;86(4):1.30. 33. https://doi.org/10.1007/s11538-024-01263-7

Author

Cifuentes, Diego ; Draisma, Jan ; Henriksson, Oskar ; Korchmaros, Annachiara ; Kubjas, Kaie. / 3D Genome Reconstruction from Partially Phased Hi-C Data. I: Bulletin of Mathematical Biology. 2024 ; Bind 86, Nr. 4. s. 1.30.

Bibtex

@article{dbdec81ce7ff45afb5aa09096e192c08,
title = "3D Genome Reconstruction from Partially Phased Hi-C Data",
abstract = "The 3-dimensional (3D) structure of the genome is of significant importance for many cellular processes. In this paper, we study the problem of reconstructing the 3D structure of chromosomes from Hi-C data of diploid organisms, which poses additional challenges compared to the better-studied haploid setting. With the help of techniques from algebraic geometry, we prove that a small amount of phased data is sufficient to ensure finite identifiability, both for noiseless and noisy data. In the light of these results, we propose a new 3D reconstruction method based on semidefinite programming, paired with numerical algebraic geometry and local optimization. The performance of this method is tested on several simulated datasets under different noise levels and with different amounts of phased data. We also apply it to a real dataset from mouse X chromosomes, and we are then able to recover previously known structural features.",
keywords = "13P25, 14P05, 3D genome organization, 65H14, 90C90, 92-08, 92E10, Applied algebraic geometry, Diploid organisms, Hi-C, Numerical algebraic geometry",
author = "Diego Cifuentes and Jan Draisma and Oskar Henriksson and Annachiara Korchmaros and Kaie Kubjas",
note = "Publisher Copyright: {\textcopyright} The Author(s) 2024.",
year = "2024",
doi = "10.1007/s11538-024-01263-7",
language = "English",
volume = "86",
pages = "1.30",
journal = "Bulletin of Mathematical Biology",
issn = "0092-8240",
publisher = "Springer",
number = "4",

}

RIS

TY - JOUR

T1 - 3D Genome Reconstruction from Partially Phased Hi-C Data

AU - Cifuentes, Diego

AU - Draisma, Jan

AU - Henriksson, Oskar

AU - Korchmaros, Annachiara

AU - Kubjas, Kaie

N1 - Publisher Copyright: © The Author(s) 2024.

PY - 2024

Y1 - 2024

N2 - The 3-dimensional (3D) structure of the genome is of significant importance for many cellular processes. In this paper, we study the problem of reconstructing the 3D structure of chromosomes from Hi-C data of diploid organisms, which poses additional challenges compared to the better-studied haploid setting. With the help of techniques from algebraic geometry, we prove that a small amount of phased data is sufficient to ensure finite identifiability, both for noiseless and noisy data. In the light of these results, we propose a new 3D reconstruction method based on semidefinite programming, paired with numerical algebraic geometry and local optimization. The performance of this method is tested on several simulated datasets under different noise levels and with different amounts of phased data. We also apply it to a real dataset from mouse X chromosomes, and we are then able to recover previously known structural features.

AB - The 3-dimensional (3D) structure of the genome is of significant importance for many cellular processes. In this paper, we study the problem of reconstructing the 3D structure of chromosomes from Hi-C data of diploid organisms, which poses additional challenges compared to the better-studied haploid setting. With the help of techniques from algebraic geometry, we prove that a small amount of phased data is sufficient to ensure finite identifiability, both for noiseless and noisy data. In the light of these results, we propose a new 3D reconstruction method based on semidefinite programming, paired with numerical algebraic geometry and local optimization. The performance of this method is tested on several simulated datasets under different noise levels and with different amounts of phased data. We also apply it to a real dataset from mouse X chromosomes, and we are then able to recover previously known structural features.

KW - 13P25

KW - 14P05

KW - 3D genome organization

KW - 65H14

KW - 90C90

KW - 92-08

KW - 92E10

KW - Applied algebraic geometry

KW - Diploid organisms

KW - Hi-C

KW - Numerical algebraic geometry

U2 - 10.1007/s11538-024-01263-7

DO - 10.1007/s11538-024-01263-7

M3 - Journal article

C2 - 38386111

AN - SCOPUS:85185698287

VL - 86

SP - 1.30

JO - Bulletin of Mathematical Biology

JF - Bulletin of Mathematical Biology

SN - 0092-8240

IS - 4

M1 - 33

ER -

ID: 384873416