SCAN STATISTICS ON POISSON RANDOM FIELDS WITH APPLICATIONS IN GENOMICS

• 成果类型: Article
• 署名作者: Zhang, Nancy R.; Yakir, Benjamin; Xia, Li C.; Siegmund, David
• 署名单位: University of Pennsylvania; Hebrew University of Jerusalem; Stanford University; Stanford University
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/15-AOAS892
• 发表日期: 2016
• 页码: 726-755
• 关键词: paired-end; structural variation; chip-seq; RESOLUTION; DISCOVERY; alignment; models

摘要

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.