Section: New Results

Statistical study of asymmetry in cell lineage data

Participants : Benoîte de Saporta, Anne Gégout-Petit.

Simulation studies of the asymmetry in a single lineage data have shown a lack of power of the tests when the number of available generation is limited. This work proposes a rigorous methodology to study cell division data in the context of observation of several lineages. It generalizes [20] . We model the data by an asymmetric bifurcating autoregressive (BAR) process and take into account possibly missing data by modeling the genealogies with a two-type Galton Watson (GW) process. Our inference is based on several lineages, i.e. independent and identically distributed replicas of the coupled BAR and GW processes. We propose a least-squares estimator of the unknown parameters of the BAR process and an estimator of the parameters of the GW process, study their asymptotic properties and propose symmetry tests. Our results are applied on real data of Escherichia coli division.

This work is in collaboration with Laurence Marsalle of Lille 1 university. It will be soon submitted for publication.