VARIANCE-COMPONENTS MODELS FOR DEPENDENT CELL-POPULATIONS

Cells grown in culture can be tracked for several generations and meas urements taken on size or age at division and other cell characteristi cs. The observations for the offspring of each cell from a family tree of dependent data. Such cell lineage data are here modeled as repeate d measurements on different family trees arising from individual ances tor cells selected at random from a population of cultured cells. The bifurcating autoregression model is embedded in a process that allows for measurement error and variation from tree to tree. Robust methods are presented that accommodate outliers in this time-dependent and bra nching environment while allowing the statistician to interactively bu ild a variance components model for the process. The methodology is il lustrated on a substantial data set of 41 trees of EMT6 cells, with th e surprising conclusion that after removing measurement error, sister- cell lifetimes are nearly identical.