Package: PeakSegOptimal 2024.10.1

PeakSegOptimal: Optimal Segmentation Subject to Up-Down Constraints

Computes optimal changepoint models using the Poisson likelihood for non-negative count data, subject to the PeakSeg constraint: the first change must be up, second change down, third change up, etc. For more info about the models and algorithms, read "Constrained Dynamic Programming and Supervised Penalty Learning Algorithms for Peak Detection" <https://jmlr.org/papers/v21/18-843.html> by TD Hocking et al.

Authors:Toby Dylan Hocking [aut, cre]

PeakSegOptimal_2024.10.1.tar.gz
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PeakSegOptimal_2024.10.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
PeakSegOptimal/json (API)

# Install 'PeakSegOptimal' in R:
install.packages('PeakSegOptimal', repos = c('https://tdhock.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/tdhock/peaksegoptimal/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

cpp

3.69 score 6 stars 41 scripts 289 downloads 7 exports 19 dependencies

Last updated from:40b762a4ac. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK182
linux-devel-x86_64OK194
source / vignettesOK266
linux-release-arm64OK169
linux-release-x86_64OK210
macos-release-arm64OK125
macos-release-x86_64OK292
macos-oldrel-arm64OK115
macos-oldrel-x86_64OK254
windows-develOK289
windows-releaseOK350
windows-oldrelOK284
wasm-releaseOK106

Exports:oracleModelComplexityPeakSegFPOPPeakSegFPOPchromPeakSegPDPAPeakSegPDPAchromPeakSegPDPAInfPoissonLoss

Dependencies:clicpp11data.tablefarverggplot2gluegtableisobandlabelinglifecyclepenaltyLearningR6RColorBrewerrlangS7scalesvctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
H3K4me3_PGP_immune ChIP-seq data set chunk 24H3K4me3_PGP_immune_chunk24
H3K4me3_XJ_immune chunk 1H3K4me3_XJ_immune_chunk1
oracleModelComplexityoracleModelComplexity
PeakSegFPOPPeakSegFPOP
PeakSegFPOPchromPeakSegFPOPchrom
PeakSegPDPAPeakSegPDPA
PeakSegPDPAchromPeakSegPDPAchrom
PeakSegPDPAInfPeakSegPDPAInf
PoissonLossPoissonLoss