PeakSegDP: Dynamic Programming Algorithm for Peak Detection in ChIP-Seq Data

A quadratic time dynamic programming algorithm can be used to compute an approximate solution to the problem of finding the most likely changepoints with respect to the Poisson likelihood, subject to a constraint on the number of segments, and the changes which must alternate: up, down, up, down, etc. For more info read <> "PeakSeg: constrained optimal segmentation and supervised penalty learning for peak detection in count data" by TD Hocking et al, proceedings of ICML2015.

Version: 2024.1.24
Depends: R (≥ 2.10)
Suggests: ggplot2 (≥ 2.0), testthat, penaltyLearning
Published: 2024-01-24
DOI: 10.32614/CRAN.package.PeakSegDP
Author: Toby Dylan Hocking, Guillem Rigaill
Maintainer: Toby Dylan Hocking <toby.hocking at>
License: GPL-3
NeedsCompilation: yes
Materials: NEWS
CRAN checks: PeakSegDP results


Reference manual: PeakSegDP.pdf


Package source: PeakSegDP_2024.1.24.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): PeakSegDP_2024.1.24.tgz, r-oldrel (arm64): PeakSegDP_2024.1.24.tgz, r-release (x86_64): PeakSegDP_2024.1.24.tgz, r-oldrel (x86_64): PeakSegDP_2024.1.24.tgz
Old sources: PeakSegDP archive

Reverse dependencies:

Reverse suggests: PeakSegOptimal


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