Open Access
March 2013 Multiple testing of local maxima for detection of peaks in ChIP-Seq data
Armin Schwartzman, Andrew Jaffe, Yulia Gavrilov, Clifford A. Meyer
Ann. Appl. Stat. 7(1): 471-494 (March 2013). DOI: 10.1214/12-AOAS594


A topological multiple testing approach to peak detection is proposed for the problem of detecting transcription factor binding sites in ChIP-Seq data. After kernel smoothing of the tag counts over the genome, the presence of a peak is tested at each observed local maximum, followed by multiple testing correction at the desired false discovery rate level. Valid $p$-values for candidate peaks are computed via Monte Carlo simulations of smoothed Poisson sequences, whose background Poisson rates are obtained via linear regression from a Control sample at two different scales. The proposed method identifies nearby binding sites that other methods do not.


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Armin Schwartzman. Andrew Jaffe. Yulia Gavrilov. Clifford A. Meyer. "Multiple testing of local maxima for detection of peaks in ChIP-Seq data." Ann. Appl. Stat. 7 (1) 471 - 494, March 2013.


Published: March 2013
First available in Project Euclid: 9 April 2013

zbMATH: 06171280
MathSciNet: MR3086427
Digital Object Identifier: 10.1214/12-AOAS594

Keywords: False discovery rate , kernel smoothing , matched filter , Poisson sequence , topological inference

Rights: Copyright © 2013 Institute of Mathematical Statistics

Vol.7 • No. 1 • March 2013
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