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The detection of local genomic signals using high-throughput DNA sequencingdata can be cast as a problem of scanning a Poisson random field for localchanges in the rate of the process. We propose a likelihood-based framework forfor such scans, and derive formulas for false positive rate control and powercalculations. The framework can also accommodate mixtures of Poisson processesto deal with over-dispersion. As a specific, detailed example, we consider thedetection of insertions and deletions by paired-end DNA-sequencing. We proposeseveral statistics for this problem, compare their power under currentexperimental designs, and illustrate their application on an Illumina PlatinumGenomes data set.

Scanning a Poisson Random Field for Local Signals