Open Access
June 2016 Scan statistics on Poisson random fields with applications in genomics
Nancy R. Zhang, Benjamin Yakir, Li C. Xia, David Siegmund
Ann. Appl. Stat. 10(2): 726-755 (June 2016). DOI: 10.1214/15-AOAS892


The detection of local genomic signals using high-throughput DNA sequencing data can be cast as a problem of scanning a Poisson random field for local changes in the rate of the process. We propose a likelihood-based framework for such scans, and derive formulas for false positive rate control and power calculations. The framework can also accommodate modified processes that involve overdispersion. As a specific, detailed example, we consider the detection of insertions and deletions by paired-end DNA-sequencing. We propose several statistics for this problem, compare their power under current experimental designs, and illustrate their application on an Illumina Platinum Genomes data set.


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Nancy R. Zhang. Benjamin Yakir. Li C. Xia. David Siegmund. "Scan statistics on Poisson random fields with applications in genomics." Ann. Appl. Stat. 10 (2) 726 - 755, June 2016.


Received: 1 April 2014; Revised: 1 September 2015; Published: June 2016
First available in Project Euclid: 22 July 2016

zbMATH: 06625667
MathSciNet: MR3528358
Digital Object Identifier: 10.1214/15-AOAS892

Keywords: change-point detection , next-generation sequencing , Poisson processes , scan statistics , structural variation

Rights: Copyright © 2016 Institute of Mathematical Statistics

Vol.10 • No. 2 • June 2016
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