ESTIMATING CLONAL HETEROGENEITY AND INTEREXPERIMENT VARIABILITY WITH THE BIFURCATING AUTOREGRESSIVE MODEL FOR CELL LINEAGE DATA

We utilize an extension of the variance-components models for cell lin eage data in Huggins and Staudte [1] (R. M. Huggins and R. G. Staudte, Variance components models for dependent cell populations. J. Am. Sta t. Assoc. 89:19-29 (1994)) to analyze NIH3T3 cells grown in two differ ent media. This modeling approach has the advantage of a simple built- in correlation structure between familial members and allows for estim ating experimental effects, rather than treating them as random effect s. In addition, this methodology gives robust estimates of model param eters together with standard errors required for statistical inference . The importance of clonal heterogeneity and interexperiment variabili ty in modeling eukaryotic cell cycles was previously pointed out by Ku czek and Axelrod [2] (T. Kuczek and D. E. Axelrod, The importance of c lonal heterogeneity and interexperimental variability in modeling the eukaryotic cell cycle. Math. Biosci. 79:87-96 (1986)). This analysis c onfirms significantly positive sister-sister correlation when cells ar e grown in rich or poor medium and negative mother-daughter correlatio n when cells are grown in poor medium. However, for cells grown in ric h medium, Kuczek and Axelrod's analysis gives negative mother-daughter correlations, whereas this analysis gives significant positive mother -daughter correlations. (C) Elsevier Science Inc., 1997.