Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Bayesian Estimation of 3D Chromosomal Structure from Single Cell Hi-C Data

Michael Rosenthal, Darshan Bryner, Fred Huffer, Shane Evans, Anuj Srivastava, Nicola Neretti
doi: https://doi.org/10.1101/316265
Michael Rosenthal
1Naval Surface Warfare Center, Panama City, FL
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Darshan Bryner
1Naval Surface Warfare Center, Panama City, FL
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Fred Huffer
2Department of Statistics, Florida State University, Tallahassee, FL
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Shane Evans
3Center for Computational Molecular Biology, Brown University, Providence, RI
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Anuj Srivastava
2Department of Statistics, Florida State University, Tallahassee, FL
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: anuj@stat.fsu.edu nicolaneretti@brown.edu
Nicola Neretti
4Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, RI
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: anuj@stat.fsu.edu nicolaneretti@brown.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

The problem of 3D chromosome structure inference from Hi-C datasets is important and challenging. While bulk Hi-C datasets contain contact information derived from millions of cells, and can capture major structural features shared by the majority of cells in the sample, they do not provide information about local variability between cells. Single cell Hi-C can overcome this problem, but contact matrices are generally very sparse, making structural inference more problematic. We have developed a Bayesian multiscale approach, named SIMBA3D, to infer 3D structures of chromosomes from single cell Hi-C while including the bulk Hi-C data and some regularization terms as a prior. We study the landscape of solutions for each single-cell Hi-C dataset as a function of prior strength and demonstrate clustering of solutions using data from the same cell.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted May 07, 2018.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Bayesian Estimation of 3D Chromosomal Structure from Single Cell Hi-C Data
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Bayesian Estimation of 3D Chromosomal Structure from Single Cell Hi-C Data
Michael Rosenthal, Darshan Bryner, Fred Huffer, Shane Evans, Anuj Srivastava, Nicola Neretti
bioRxiv 316265; doi: https://doi.org/10.1101/316265
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
Bayesian Estimation of 3D Chromosomal Structure from Single Cell Hi-C Data
Michael Rosenthal, Darshan Bryner, Fred Huffer, Shane Evans, Anuj Srivastava, Nicola Neretti
bioRxiv 316265; doi: https://doi.org/10.1101/316265

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (2428)
  • Biochemistry (4784)
  • Bioengineering (3328)
  • Bioinformatics (14656)
  • Biophysics (6629)
  • Cancer Biology (5162)
  • Cell Biology (7417)
  • Clinical Trials (138)
  • Developmental Biology (4355)
  • Ecology (6869)
  • Epidemiology (2057)
  • Evolutionary Biology (9903)
  • Genetics (7338)
  • Genomics (9509)
  • Immunology (4545)
  • Microbiology (12657)
  • Molecular Biology (4936)
  • Neuroscience (28280)
  • Paleontology (199)
  • Pathology (804)
  • Pharmacology and Toxicology (1388)
  • Physiology (2019)
  • Plant Biology (4487)
  • Scientific Communication and Education (976)
  • Synthetic Biology (1297)
  • Systems Biology (3909)
  • Zoology (725)