Inferring Spatial Organization of Individual Topologically Associated Domains via Piecewise Helical Model

The recently developed Hi-C technology enables a genome-wide view of chromosome spatial organizations, and has shed deep insights into genome structure and genome function. However, multiple sources of uncertainties make downstream data analysis and interpretation challenging. Specifically, statisti...

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Vydané v:IEEE/ACM transactions on computational biology and bioinformatics Ročník 17; číslo 2; s. 647 - 656
Hlavní autori: Zhang, Rongrong, Hu, Ming, Zhu, Yu, Qin, Zhaohui, Deng, Ke, Liu, Jun S.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States IEEE 01.03.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Animals
Bayes Theorem
Bayesian model
Bioinformatics
Biological cells
Biological system modeling
Chromatin
Chromosome spatial organizations
Chromosomes
Chromosomes - chemistry
Chromosomes - genetics
Chromosomes - ultrastructure
Computer Simulation
Data analysis
Data models
Domains
Genome - genetics
Genomes
Genomics
Genomics - methods
Hi-C data
Mathematical models
MCMC
Mice
Organizations
Outliers (statistics)
piecewise helical model
Statistical analysis
Statistical models
Structure-function relationships
Three dimensional models
Three-dimensional displays
ISSN:1545-5963, 1557-9964, 1557-9964
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Popis
Shrnutí:The recently developed Hi-C technology enables a genome-wide view of chromosome spatial organizations, and has shed deep insights into genome structure and genome function. However, multiple sources of uncertainties make downstream data analysis and interpretation challenging. Specifically, statistical models for inferring three-dimensional (3D) chromosomal structure from Hi-C data are far from their maturity. Most existing methods are highly over-parameterized, lacking clear interpretations, and sensitive to outliers. In this study, we propose a parsimonious, easy to interpret, and robust piecewise helical model for the inference of 3D chromosomal structure of individual topologically associated domain from Hi-C data. When applied to a real Hi-C dataset, the piecewise helical model not only achieves much better model fitting than existing models, but also reveals that geometric properties of chromatin spatial organization are closely related to genome function.
Bibliografia:ObjectType-Article-1
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ISSN:1545-5963
1557-9964
1557-9964
DOI:10.1109/TCBB.2018.2865349