Scanning a Poisson Random Field for Local Signals
Applications
2014-06-13 v1 Genomics
Methodology
Abstract
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 for such scans, and derive formulas for false positive rate control and power calculations. The framework can also accommodate mixtures of Poisson processes to deal with over-dispersion. 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.
Cite
@article{arxiv.1406.3258,
title = {Scanning a Poisson Random Field for Local Signals},
author = {Nancy R. Zhang and Benjamin Yakir and Charlie L. Xia and David Siegmund},
journal= {arXiv preprint arXiv:1406.3258},
year = {2014}
}