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CellTrans: An R Package to Quantify Stochastic Cell State Transitions.

Thomas Buder1,2, Andreas Deutsch1, Michael Seifert3,4

  • 1Fakultät Informatik/Mathematik, Hochschule für Technik und Wirtschaft Dresden, Dresden, Germany.

Bioinformatics and Biology Insights
|June 30, 2017
PubMed
Summary

CellTrans quantifies cell state transitions using a mathematical model, enabling predictions of cell line compositions and equilibrium states. This R package aids in understanding cell lineage dynamics from flow cytometry data.

Keywords:
Equilibrium cell state proportionsMarkov modelcell state transitionsflow cytometry experimentsfluorescence-activated cell sorting (FACS)

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Area of Science:

  • Computational Biology
  • Biophysics
  • Cell Biology

Background:

  • Cell lines maintain stable compositions in distinct states, often linked to stochastic transitions.
  • Understanding these cell state transitions is crucial for deciphering cell lineage dynamics.

Purpose of the Study:

  • To introduce CellTrans, an R package for quantifying stochastic cell state transitions.
  • To provide an automated tool for estimating transition probabilities from cell state proportion data.

Main Methods:

  • Developed a mathematical model where cell state changes occur via stochastic transitions.
  • Utilized R package CellTrans to estimate transition probabilities from fluorescence-activated cell sorting and flow cytometry data.
  • Addressed analytical challenges in quantifying cell transitions.

Main Results:

  • CellTrans successfully infers transition probabilities between cell states.
  • The package predicts future and equilibrium cell line compositions.
  • It accurately estimates the time required to reach equilibrium.

Conclusions:

  • CellTrans offers a robust method for analyzing cell state dynamics.
  • The R package facilitates deeper understanding of cell lineage and equilibrium in cell lines.
  • CellTrans is publicly available on GitHub for broader research application.