Abstract
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.
Citation
Jeremy J. Shen. Nancy R. Zhang. "Change-point model on nonhomogeneous Poisson processes with application in copy number profiling by next-generation DNA sequencing." Ann. Appl. Stat. 6 (2) 476 - 496, June 2012. https://doi.org/10.1214/11-AOAS517
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