Sean Dewar, Georg Grasegger, Kaie Kubjas, Fatemeh Mohammadi, Anthony Nixon
{"title":"Single-cell 3D genome reconstruction in the haploid setting using rigidity theory","authors":"Sean Dewar, Georg Grasegger, Kaie Kubjas, Fatemeh Mohammadi, Anthony Nixon","doi":"arxiv-2407.10700","DOIUrl":null,"url":null,"abstract":"This article considers the problem of 3-dimensional genome reconstruction for\nsingle-cell data, and the uniqueness of such reconstructions in the setting of\nhaploid organisms. We consider multiple graph models as representations of this\nproblem, and use techniques from graph rigidity theory to determine\nidentifiability. Biologically, our models come from Hi-C data, microscopy data,\nand combinations thereof. Mathematically, we use unit ball and sphere packing\nmodels, as well as models consisting of distance and inequality constraints. In\neach setting, we describe and/or derive new results on realisability and\nuniqueness. We then propose a 3D reconstruction method based on semidefinite\nprogramming and apply it to synthetic and real data sets using our models.","PeriodicalId":501070,"journal":{"name":"arXiv - QuanBio - Genomics","volume":"48 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Genomics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2407.10700","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.