Scanning a Poisson Random Field for Local Signals

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Statistics Papers
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Scan statistics
Poisson processes
change-point detection
next-generation sequencing
structural variation
Physical Sciences and Mathematics
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Zhang, Nancy R
Yakir, Benjamin
Xia, Charlie L
Siegmund, David O
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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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2016-01-01
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The Annals of Applied Statistics
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