☆ 4.4 Article

THE SCREENING AND RANKING ALGORITHM TO DETECT DNA COPY NUMBER VARIATIONS

ANNALS OF APPLIED STATISTICS (2012)

期刊

ANNALS OF APPLIED STATISTICS

卷 6, 期 3, 页码 1306-1326

出版社

INST MATHEMATICAL STATISTICS

DOI: 10.1214/12-AOAS539

关键词

Change-point detection; copy number variations; high dimensional data; screening and ranking algorithm

类别

Statistics & Probability

资金

University of Arizona Internal grant
National Institute on Drug Abuse Grant [R01-DA016750]

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Protocol

Reagent

摘要

DNA Copy number variation (CNV) has recently gained considerable interest as a source of genetic variation that likely influences phenotypic differences. Many statistical and computational methods have been proposed and applied to detect CNVs based on data that generated by genome analysis platforms. However, most algorithms are computationally intensive with complexity at least O(n(2)), where n is the number of probes in the experiments. Moreover, the theoretical properties of those existing methods are not well understood. A faster and better characterized algorithm is desirable for the ultra high throughput data. In this study, we propose the Screening and Ranking algorithm (SaRa) which can detect CNVs fast and accurately with complexity down to O(n). In addition, we characterize theoretical properties and present numerical analysis for our algorithm.

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