Identifying gene expression programs in single-cell RNA-seq data using linear correlation explanation.

Journal: Journal of biomedical informatics
PMID: 38631462

Abstract

OBJECTIVE: Gene expression analysis through single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of gene regulation in diverse cell types, tissues, and organisms. While existing methods primarily focus on identifying cell type-specific gene expression programs (GEPs), the characterization of GEPs associated with biological processes and stimuli responses remains limited. In this study, we aim to infer biologically meaningful GEPs that are associated with both cellular phenotypes and activity programs directly from scRNA-seq data.

Authors

  • Yulia I Nussbaum
    Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65201, USA.
  • K S M Tozammel Hossain
    Department of Information Science, University of North Texas, 3940 N Elm St, Denton, TX 76203, USA.
  • Jussuf Kaifi
    Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65201, USA; Department of Surgery, University of Missouri Hospital, 1 Hospital Dr., Columbia, MO 65212, USA; Harry S. Truman Memorial Veterans' Hospital, 800 Hospital Dr., Columbia, MO 65201, USA; Siteman Cancer Center, Washington University School of Medicine, 4921 Parkview Pl, St. Louis, MO 63110, USA.
  • Wesley C Warren
    Institute for Data Science & Informatics, University of Missouri, Columbia, MO 65211, USA; Department of Surgery, School of Medicine, University of Missouri, Columbia, MO 65212, USA; Department of Animal Sciences, Bond Life Sciences Center, University of Missouri, 1201 Rollins Street, Columbia, MO 65211, USA.
  • Chi-Ren Shyu
    Institute for Data Science & Informatics, University of Missouri, Columbia, MO 65211, USA; Electrical Engineering and Computer Science Department, University of Missouri, Columbia, MO 65211, USA; Department of Medicine, School of Medicine, University of Missouri, Columbia, MO 65212, USA. Electronic address: shyuc@missouri.edu.
  • Jonathan B Mitchem
    Institute for Data Science & Informatics, University of Missouri, Columbia, MO 65211, USA; Department of Surgery, School of Medicine, University of Missouri, Columbia, MO 65212, USA; Harry S. Truman Memorial Veterans' Hospital, Columbia, MO 65201, USA. Electronic address: mitchemj@health.missouri.edu.

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