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PeakSegDP
View on CRAN: Click
here
Download and install PeakSegDP package within the R console
Install from CRAN:
install.packages("PeakSegDP")
Install from Github:
library("remotes")
install_github("cran/PeakSegDP") Install by package version:
library("remotes")
install_version("PeakSegDP", "2024.1.24") Attach the package and use:
library("PeakSegDP")
Maintained by
Toby Dylan Hocking
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-06-21
Latest Update: 2024-01-24
Description:
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.
How to cite:
Toby Dylan Hocking (2017). PeakSegDP: Dynamic Programming Algorithm for Peak Detection in ChIP-Seq Data. R package version 2024.1.24, https://cran.r-project.org/web/packages/PeakSegDP. Accessed 25 Jun. 2026.
Previous versions and publish date:
2017.06.20 (2017-06-21 01:23), 2017.08.15 (2017-08-15 23:39)
Other packages that cited PeakSegDP R package
View PeakSegDP citation profile
Other R packages that PeakSegDP depends,
imports, suggests or enhances
Complete documentation for PeakSegDP
Functions, R codes and Examples using
the PeakSegDP R package
Some associated functions: GeomTallRect . H3K36me3.AM.immune.19 . H3K36me3.TDH.other.chunk3.cluster4 . H3K4me3.TDH.immune.chunk12.cluster4 . PeakSegDP . PoissonLoss . cDPA . calc.grad.list . calc.loss.from.lp.list . calc.loss.list . chr11ChIPseq . chr11first . derivs . getPath . phi.list . regression.funs .
Some associated R codes: PeakSegDP.R . PoissonLoss.R . cDPA.R . Full PeakSegDP package functions and examples
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