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September 2012 The screening and ranking algorithm to detect DNA copy number variations
Yue S. Niu, Heping Zhang
Ann. Appl. Stat. 6(3): 1306-1326 (September 2012). DOI: 10.1214/12-AOAS539

Abstract

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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Yue S. Niu. Heping Zhang. "The screening and ranking algorithm to detect DNA copy number variations." Ann. Appl. Stat. 6 (3) 1306 - 1326, September 2012. https://doi.org/10.1214/12-AOAS539

Information

Published: September 2012
First available in Project Euclid: 31 August 2012

zbMATH: 06096532
MathSciNet: MR3012531
Digital Object Identifier: 10.1214/12-AOAS539

Keywords: change-point detection , copy number variations , high dimensional data , screening and ranking algorithm

Rights: Copyright © 2012 Institute of Mathematical Statistics

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Vol.6 • No. 3 • September 2012
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