The Annals of Applied Statistics
- Ann. Appl. Stat.
- Volume 7, Number 1 (2013), 471-494.
Multiple testing of local maxima for detection of peaks in ChIP-Seq data
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.
Ann. Appl. Stat., Volume 7, Number 1 (2013), 471-494.
First available in Project Euclid: 9 April 2013
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Schwartzman, Armin; Jaffe, Andrew; Gavrilov, Yulia; Meyer, Clifford A. Multiple testing of local maxima for detection of peaks in ChIP-Seq data. Ann. Appl. Stat. 7 (2013), no. 1, 471--494. doi:10.1214/12-AOAS594. https://projecteuclid.org/euclid.aoas/1365527207