Statistics Papers

Document Type

Journal Article

Date of this Version

2016

Publication Source

The Annals of Applied Statistics

Volume

10

Issue

2

Start Page

726

Last Page

755

DOI

10.1214/15-AOAS892

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 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.

Copyright/Permission Statement

The original and published work is available at: https://projecteuclid.org/euclid.aoas/1469199891#abstract

Keywords

Scan statistics, Poisson processes, change-point detection, next-generation sequencing, structural variation

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Date Posted: 27 November 2017

This document has been peer reviewed.