Estimating clonal heterogeneity and interexperiment variability with the bifurcating autoregressive model for cell lineage data

R. G. Staudte, R. M. Huggins, J. Zhang, D. E. Axelrod, M. Kimmel

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16 Scopus citations

Abstract

We utilize an extension of the variance-components models for cell lineage data in Huggins and Staudte [1] (R. M. Huggins and R. G. Staudte, Variance components models for dependent cell populations. J. Am. Stat. Assoc. 89:19-29 (1994)) to analyze NIH3T3 cells grown in two different media. This modeling approach has the advantage of a simple built-in correlation structure between familial members and allows for estimating experimental effects, rather than treating them as random effects. In addition, this methodology gives robust estimates of model parameters together with standard errors required for statistical inference. The importance of clonal heterogeneity and interexperiment variability in modeling eukaryotic cell cycles was previously pointed out by Kuczek and Axelrod [2] (T. Kuczek and D. E Axelrod. The importance of clonal heterogeneity and interexperimental variability in modeling the eukaryotic cell cycle. Math., Biosci. 79:87-96 (1986)). This analysis confirms significantly positive sister-sister correlation when cells are grown in rich or poor medium and negative mother- daughter correlation when cells are grown in poor medium. However, for cells grown in rich medium, Kuczek and Axelrod's analysis gives negative mother- daughter correlations, whereas this analysis gives significant positive mother-daughter correlations.

Original languageEnglish (US)
Pages (from-to)103-121
Number of pages19
JournalMathematical Biosciences
Volume143
Issue number2
DOIs
StatePublished - Jul 15 1997

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modeling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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