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NucHMM: a method for quantitative modeling of nucleosome organization identifying functional nucleosome states distinctly associated with splicing potentiality.

Kun FangTianbao LiYufei HuangVictor X Jin
Published in: Genome biology (2021)
We develop a novel computational method, NucHMM, to identify functional nucleosome states associated with cell type-specific combinatorial histone marks and nucleosome organization features such as phasing, spacing and positioning. We test it on publicly available MNase-seq and ChIP-seq data in MCF7, H1, and IMR90 cells and identify 11 distinct functional nucleosome states. We demonstrate these nucleosome states are distinctly associated with the splicing potentiality of skipping exons. This advances our understanding of the chromatin function at the nucleosome level and offers insights into the interplay between nucleosome organization and splicing processes.
Keyphrases
  • genome wide
  • gene expression
  • dna damage
  • single cell
  • transcription factor
  • rna seq
  • high throughput
  • oxidative stress
  • machine learning
  • big data
  • deep learning
  • electronic health record
  • cell death