We propose a flexible change-point model for inhomogeneous Poisson Processes, which arise naturally from next-generation DNA sequencing, and derive score and generalized likelihood statistics for shifts in intensity functions. We construct a modified Bayesian information criterion (mBIC) to guide model selection, and point-wise approximate Bayesian confidence intervals for assessing the confidence in the segmentation. The model is applied to DNA Copy Number profiling with sequencing data and evaluated on simulated spike-in and real data sets.
"Change-point model on nonhomogeneous Poissonprocesses with application in copy number profiling by next-generationDNA sequencing." Ann. Appl. Stat. 6 (2) 476 - 496, June 2012. https://doi.org/10.1214/11-AOAS517