• Media type: E-Article
  • Title: Posterior inference of Hi-C contact frequency through sampling
  • Contributor: Zhang, Yanlin; Cameron, Christopher J. F.; Blanchette, Mathieu
  • imprint: Frontiers Media SA, 2024
  • Published in: Frontiers in Bioinformatics
  • Language: Not determined
  • DOI: 10.3389/fbinf.2023.1285828
  • ISSN: 2673-7647
  • Keywords: Environmental Engineering
  • Origination:
  • Footnote:
  • Description: <jats:p>Hi-C is one of the most widely used approaches to study three-dimensional genome conformations. Contacts captured by a Hi-C experiment are represented in a contact frequency matrix. Due to the limited sequencing depth and other factors, Hi-C contact frequency matrices are only approximations of the true interaction frequencies and are further reported without any quantification of uncertainty. Hence, downstream analyses based on Hi-C contact maps (e.g., TAD and loop annotation) are themselves point estimations. Here, we present the Hi-C interaction frequency sampler (HiCSampler) that reliably infers the posterior distribution of the interaction frequency for a given Hi-C contact map by exploiting dependencies between neighboring loci. Posterior predictive checks demonstrate that HiCSampler can infer highly predictive chromosomal interaction frequency. Summary statistics calculated by HiCSampler provide a measurement of the uncertainty for Hi-C experiments, and samples inferred by HiCSampler are ready for use by most downstream analysis tools off the shelf and permit uncertainty measurements in these analyses without modifications.</jats:p>
  • Access State: Open Access