Bayesian detection of embryonic gene expression onset in C. elegans

Jie Hu*, Zhongying Zhao, Hari Krishna Yalamanchili, Junwen Wang, Kenny Ye, Xiaodan Fan*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

7 Citations (Scopus)


To study how a zygote develops into an embryo with different tissues, large-scale 4D confocal movies of C. elegans embryos have been produced recently by experimental biologists. However, the lack of principled statistical methods for the highly noisy data has hindered the comprehensive analysis of these data sets. We introduced a probabilistic change point model on the cell lineage tree to estimate the embryonic gene expression onset time. A Bayesian approach is used to fit the 4D confocal movies data to the model. Subsequent classification methods are used to decide a model selection threshold and further refine the expression onset time from the branch level to the specific cell time level. Extensive simulations have shown the high accuracy of our method. Its application on real data yields both previously known results and new findings.

Original languageEnglish
Pages (from-to)950-968
Number of pages19
JournalAnnals of Applied Statistics
Issue number2
Publication statusPublished - Jun 2015

Scopus Subject Areas

  • Statistics and Probability
  • Modelling and Simulation
  • Statistics, Probability and Uncertainty

User-Defined Keywords

  • 4D confocal microscopy
  • Bayesian method
  • Change point detection
  • Embryonic onset


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