Title: Bayesian Detection of Abnormal ADS in Mutant Caenorhabditis elegans Embryos,
Abstract: Cell division timing is critical for cell fate specification and
morphogenesis during embryogenesis. How division timings are regulated among
cells during development is poorly understood. Here we focus on the comparison
of asynchrony of division between sister cells (ADS) between wild-type and
mutant individuals of Caenorhabditis elegans. Since the replicate number of
mutant individuals of each mutated gene, usually one, is far smaller than that
of wild-type, direct comparison of two distributions of ADS between wild-type
and mutant type, such as Kolmogorov- Smirnov test, is not feasible. On the
other hand, we find that sometimes ADS is correlated with the life span of
corresponding mother cell in wild-type. Hence, we apply a semiparametric
Bayesian quantile regression method to estimate the 95% confidence interval
curve of ADS with respect to life span of mother cell of wild-type individuals.
Then, mutant-type ADSs outside the corresponding confidence interval are
selected out as abnormal one with a significance level of 0.05. Simulation
study demonstrates the accuracy of our method and Gene Enrichment Analysis
validates the results of real data sets.