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Title page for ETD etd-03302018-121504


Type of Document Dissertation
Author Herring, Charles Albert
Author's Email Address charles.a.herring@vanderbilt.edu
URN etd-03302018-121504
Title Cell Fate Relationships Mapped by p-Creode Trajectory Analysis of Single-cell Data
Degree PhD
Department Chemical and Physical Biology
Advisory Committee
Advisor Name Title
Vito Quaranta Committee Chair
Erin Rericha Committee Member
Gregor Neuert Committee Member
John Anthony Capra Committee Member
Ken Lau Committee Member
Keywords
  • differentiation hierarchies
  • trajectories
  • pseudo-time analysis
  • single-cell RNA-seq
  • intestine and colon
  • mass cytometry
  • graph theory
  • tuft cells
  • cell-state transitions
  • single-cell biology
Date of Defense 2018-03-19
Availability unrestricted
Abstract
Modern single-cell technologies allow multiplexed sampling of cellular states within a tissue. However, computational tools that can infer developmental cell-state transitions reproducibly from such single-cell data are lacking. Here, introduced is p-Creode, an unsupervised algorithm that produces multi-branching graphs from single-cell data, compares graphs with differing topologies, and infers a statistically robust hierarchy of cell-state transitions that define developmental trajectories. p-Creode is applied to mass cytometry, multiplex immunofluorescence, and single-cell RNA-seq data. As a test case, we validate cell-state-transition trajectories predicted by p-Creode for intestinal tuft cells, a rare, chemosensory cell type. We clarify that tuft cells are specified outside of the Atoh1-dependent secretory lineage in the small intestine. However, p-Creode also predicts, and we confirm, that tuft cells arise from an alternative, Atoh1-driven developmental program in the colon. These studies introduce p-Creode as a reliable method for analyzing large datasets that depict branching transition trajectories.

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