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A Unified Bayesian Framework for Bi-overlapping-Clustering Multi-omics Data via Sparse Matrix Factorization

Author

Listed:
  • Fangting Zhou

    (Renmin University of China
    Texas A&M University)

  • Kejun He

    (Renmin University of China)

  • James J. Cai

    (Texas A&M University)

  • Laurie A. Davidson

    (Texas A&M University
    Texas A &M University)

  • Robert S. Chapkin

    (Texas A&M University
    Texas A &M University)

  • Yang Ni

    (Texas A&M University)

Abstract

The advances of modern sequencing techniques have generated an unprecedented amount of multi-omics data which provide great opportunities to quantitatively explore functional genomes from different but complementary perspectives. However, distinct modalities/sequencing technologies generate diverse types of data which greatly complicate statistical modeling because uniquely optimized methods are required for handling each type of data. In this paper, we propose a unified framework for Bayesian nonparametric matrix factorization that infers overlapping bi-clusters for multi-omics data. The proposed method adaptively discretizes different types of observations into common latent states on which cluster structures are built hierarchically. The proposed Bayesian nonparametric method is able to automatically determine the number of clusters. We demonstrate the utility of the proposed method using simulation studies and applications to a single-cell RNA-sequencing dataset, a combination of single-cell RNA-sequencing and single-cell ATAC-sequencing dataset, a bulk RNA-sequencing dataset, and a DNA methylation dataset which reveal several interesting findings that are consistent with biological literature.

Suggested Citation

  • Fangting Zhou & Kejun He & James J. Cai & Laurie A. Davidson & Robert S. Chapkin & Yang Ni, 2023. "A Unified Bayesian Framework for Bi-overlapping-Clustering Multi-omics Data via Sparse Matrix Factorization," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(3), pages 669-691, December.
    • Handle: RePEc:spr:stabio:v:15:y:2023:i:3:d:10.1007_s12561-022-09350-w
    DOI: 10.1007/s12561-022-09350-w
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    References listed on IDEAS

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