Bayesian detection of embryonic gene expression onset in C. elegans

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

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

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 (US)
Pages (from-to)950-968
Number of pages19
JournalAnnals of Applied Statistics
Volume9
Issue number2
DOIs
StatePublished - Jun 1 2015
Externally publishedYes

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Keywords

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

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Modeling and Simulation
  • Statistics and Probability

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