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Single Cell Fate Mapping in Zebrafish
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Computational Tools for Quantifying Concordance in Single-Cell Fate.

J A Cornwell1, R E Nordon2

  • 1Department of Life Sciences, Faculty of Dentistry, University of Sydney, Westmead Centre for Oral Health, Westmead Hospital, Westmead, NSW, Australia.

Methods in Molecular Biology (Clifton, N.J.)
|May 8, 2019
PubMed
Summary
This summary is machine-generated.

Understanding cell fate requires probabilistic modeling. Competing risks statistics quantify cell fate concordance, revealing how external and inherited factors influence cell development and differentiation.

Keywords:
Clonal analysisCompeting risksConcordanceSingle-cell fate mapping

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Area of Science:

  • Cell biology
  • Quantitative biology
  • Statistical modeling

Background:

  • Cells are dynamic systems influenced by extrinsic and intrinsic factors.
  • Cell fate decisions often appear random due to heterogeneity and environmental fluctuations.
  • Accurate models of cell growth and differentiation require methods to quantify heterogeneous population fates.

Purpose of the Study:

  • To develop a probabilistic modeling approach for quantifying cell fate outcomes.
  • To differentiate between random and deterministic cell behaviors.
  • To model the deterministic effects of environment and inheritance on cell fate.

Main Methods:

  • Application of competing risks statistics, a branch of survival statistics.
  • Quantification of cell fate concordance using cell lifetime data.
  • Estimation of cause-specific cumulative incidence functions.

Main Results:

  • Competing risks modeling provides an unbiased and robust approach to cell fate analysis.
  • This method quantifies cell fate concordance from cell lifetime data.
  • It estimates the impact of extrinsic and heritable factors on cell fate.

Conclusions:

  • Competing risks modeling is a powerful tool for understanding cell growth and differentiation.
  • It offers a robust statistical framework for analyzing cell fate in heterogeneous populations.
  • This approach helps disentangle the roles of nature and nurture in cell development.