PeakSegDisk: Disk-Based Constrained Change-Point Detection

Disk-based implementation of Functional Pruning Optimal Partitioning with up-down constraints <arXiv:1810.00117> for single-sample peak calling (independently for each sample and genomic problem), can handle huge data sets (10^7 or more).

Version: 2019.9.27
Depends: R (≥ 2.10)
Imports: data.table (≥ 1.9.8)
Suggests: testthat, ggplot2, future.apply, future, knitr
Published: 2019-11-18
Author: Toby Dylan Hocking
Maintainer: Toby Dylan Hocking <toby.hocking at r-project.org>
BugReports: http://github.com/tdhock/PeakSegDisk/issues
License: GPL-3
URL: http://github.com/tdhock/PeakSegDisk
NeedsCompilation: yes
Materials: NEWS
CRAN checks: PeakSegDisk results

Downloads:

Reference manual: PeakSegDisk.pdf
Vignettes: Examples
Spatial correlation
Worst case time complexity
Package source: PeakSegDisk_2019.9.27.tar.gz
Windows binaries: r-devel: PeakSegDisk_2019.9.27.zip, r-release: PeakSegDisk_2019.9.27.zip, r-oldrel: PeakSegDisk_2019.9.27.zip
macOS binaries: r-release: PeakSegDisk_2019.9.27.tgz, r-oldrel: PeakSegDisk_2019.9.27.tgz
Old sources: PeakSegDisk archive

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