Jointly segment several ChIP-seq samples to find the peaks which are the same and different across samples. The fast approximate maximum Poisson likelihood algorithm is described in "PeakSegJoint: fast supervised peak detection via joint segmentation of multiple count data samples" <arXiv:1506.01286> by TD Hocking and G Bourque.
| Version: | 2022.4.6 |
| Depends: | R (≥ 2.14) |
| Imports: | PeakError, parallel, penaltyLearning |
| Suggests: | testthat, ggplot2 (≥ 2.0), microbenchmark |
| Published: | 2022-04-07 |
| Author: | Toby Dylan Hocking |
| Maintainer: | Toby Dylan Hocking <toby.hocking at r-project.org> |
| BugReports: | https://github.com/tdhock/PeakSegJoint/issues |
| License: | GPL-3 |
| URL: | https://github.com/tdhock/PeakSegJoint |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| CRAN checks: | PeakSegJoint results |
| Reference manual: | PeakSegJoint.pdf |
| Package source: | PeakSegJoint_2022.4.6.tar.gz |
| Windows binaries: | r-devel: PeakSegJoint_2022.4.6.zip, r-release: PeakSegJoint_2022.4.6.zip, r-oldrel: PeakSegJoint_2018.10.3.zip |
| macOS binaries: | r-release (arm64): PeakSegJoint_2022.4.6.tgz, r-oldrel (arm64): PeakSegJoint_2022.4.6.tgz, r-release (x86_64): PeakSegJoint_2022.4.6.tgz, r-oldrel (x86_64): PeakSegJoint_2022.4.6.tgz |
| Old sources: | PeakSegJoint archive |
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