Chromatyping: Reconstructing Nucleosome Profiles from NOMe Sequencing Data

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10812)

Abstract

Measuring nucleosome positioning in cells is crucial for the analysis of epigenetic gene regulation. Reconstruction of nucleosome profiles of individual cells or subpopulations of cells remains challenging because most genome-wide assays measure nucleosome positioning and DNA accessibility for thousands of cells using bulk sequencing. Here we use characteristics of the NOMe-sequencing assay to derive a new approach, called ChromaClique, for deconvolution of different nucleosome profiles (chromatypes) from cell subpopulations of one NOMe-seq measurement. ChromaClique uses a maximal clique enumeration algorithm on a newly defined NOMe read graph that is able to group reads according to their nucleosome profiles. We show that the edge probabilities of that graph can be efficiently computed using Hidden Markov Models. We demonstrate using simulated data that ChromaClique is more accurate than a related method and scales favorably, allowing genome-wide analyses of chromatypes in cell subpopulations. Software is available at https://github.com/shounak1990/ChromaClique under MIT license.

Keywords

NOMe-seq Max clique enumeration Epigenetics HMMs 

Notes

Acknowledgments

We thank Karl Nordström, Gilles Gasparoni and Jörn Walter for providing access to the HepG2 NOMe-seq data.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Cluster of Excellence for Multimodal Computing and InteractionSaarland University, Saarland Informatics Campus E1.7SaarbrückenGermany
  2. 2.Max Planck Institute for InformaticsSaarland Informatics Campus E1.4SaarbrückenGermany
  3. 3.Center for BioinformaticsSaarland University, Saarland Informatics Campus E2.1SaarbrückenGermany
  4. 4.Gene CenterLudwig-Maximilians-Universität MünchenMunichGermany

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