  The availability of a large number of assembled genomes opens the way to
study the evolution of syntenic character within a phylogenetic context. The
DeCo algorithm, recently introduced by B{\'e}rard et al. allows the computation
of parsimonious evolutionary scenarios for gene adjacencies, from pairs of
reconciled gene trees. Following the approach pioneered by Sturmfels and
Pachter, we describe how to modify the DeCo dynamic programming algorithm to
identify classes of cost schemes that generates similar parsimonious
evolutionary scenarios for gene adjacencies, as well as the robustness to
changes to the cost scheme of evolutionary events of the presence or absence of
specific ancestral gene adjacencies. We apply our method to six thousands
mammalian gene families, and show that computing the robustness to changes to
cost schemes provides new and interesting insights on the evolution of gene
adjacencies and the DeCo model.

Quantitative Methods;Populations and Evolution