  In the course of animal development, the shape of tissue emerges in part from
mechanical and biochemical interactions between cells. Measuring stress in
tissue is essential for studying morphogenesis and its physical constraints.
Experimental measurements of stress reported thus far have been invasive,
indirect, or local. One theoretical approach is force inference from cell
shapes and connectivity, which is non-invasive, can provide a space-time map of
stress and relies on prefactors. Here, to validate force- inference methods, we
performed a comparative study of them. Three force-inference methods, which
differ in their approach of treating indefiniteness in an inverse problem
between cell shapes and forces, were tested by using two artificial and two
experimental data sets. Our results using different datasets consistently
indicate that our Bayesian force inference, by which cell-junction tensions and
cell pressures are simultaneously estimated, performs best in terms of accuracy
and robustness. Moreover, by measuring the stress anisotropy and relaxation, we
cross-validated the force inference and the global annular ablation of tissue,
each of which relies on different prefactors. A practical choice of
force-inference methods in distinct systems of interest is discussed.
