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Interactive analysis of single-cell epigenomic landscapes with ChromSCape

Author

Listed:
  • Pacôme Prompsy

    (CNRS UMR3244, Institut Curie, PSL Research University
    Translational Research Department, Institut Curie, PSL Research University)

  • Pia Kirchmeier

    (CNRS UMR3244, Institut Curie, PSL Research University
    Translational Research Department, Institut Curie, PSL Research University)

  • Justine Marsolier

    (CNRS UMR3244, Institut Curie, PSL Research University
    Translational Research Department, Institut Curie, PSL Research University)

  • Marc Deloger

    (INSERM U900, Institut Curie, PSL Research University, Mines ParisTech)

  • Nicolas Servant

    (INSERM U900, Institut Curie, PSL Research University, Mines ParisTech)

  • Céline Vallot

    (CNRS UMR3244, Institut Curie, PSL Research University
    Translational Research Department, Institut Curie, PSL Research University)

Abstract

Chromatin modifications orchestrate the dynamic regulation of gene expression during development and in disease. Bulk approaches have characterized the wide repertoire of histone modifications across cell types, detailing their role in shaping cell identity. However, these population-based methods do not capture cell-to-cell heterogeneity of chromatin landscapes, limiting our appreciation of the role of chromatin in dynamic biological processes. Recent technological developments enable the mapping of histone marks at single-cell resolution, opening up perspectives to characterize the heterogeneity of chromatin marks in complex biological systems over time. Yet, existing tools used to analyze bulk histone modifications profiles are not fit for the low coverage and sparsity of single-cell epigenomic datasets. Here, we present ChromSCape, a user-friendly interactive Shiny/R application distributed as a Bioconductor package, that processes single-cell epigenomic data to assist the biological interpretation of chromatin landscapes within cell populations. ChromSCape analyses the distribution of repressive and active histone modifications as well as chromatin accessibility landscapes from single-cell datasets. Using ChromSCape, we deconvolve chromatin landscapes within the tumor micro-environment, identifying distinct H3K27me3 landscapes associated with cell identity and breast tumor subtype.

Suggested Citation

  • Pacôme Prompsy & Pia Kirchmeier & Justine Marsolier & Marc Deloger & Nicolas Servant & Céline Vallot, 2020. "Interactive analysis of single-cell epigenomic landscapes with ChromSCape," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-19542-x
    DOI: 10.1038/s41467-020-19542-x
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    Cited by:

    1. Anjun Ma & Xiaoying Wang & Jingxian Li & Cankun Wang & Tong Xiao & Yuntao Liu & Hao Cheng & Juexin Wang & Yang Li & Yuzhou Chang & Jinpu Li & Duolin Wang & Yuexu Jiang & Li Su & Gang Xin & Shaopeng Gu, 2023. "Single-cell biological network inference using a heterogeneous graph transformer," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    2. Alan Yue Yang Teo & Jordan W. Squair & Gregoire Courtine & Michael A. Skinnider, 2024. "Best practices for differential accessibility analysis in single-cell epigenomics," Nature Communications, Nature, vol. 15(1), pages 1-19, December.

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