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
<http://proceedings.mlr.press/v37/hocking15.html>
"PeakSeg: constrained optimal segmentation and supervised penalty learning
for peak detection in count data" by TD Hocking et al,
proceedings of ICML2015.
| Version: |
2017.08.15 |
| Depends: |
R (≥ 2.10) |
| Suggests: |
ggplot2 (≥ 2.0), testthat, penaltyLearning |
| Published: |
2017-08-15 |
| Author: |
Toby Dylan Hocking, Guillem Rigaill |
| Maintainer: |
Toby Dylan Hocking <toby.hocking at r-project.org> |
| License: |
GPL-3 |
| NeedsCompilation: |
yes |
| Materials: |
NEWS |
| CRAN checks: |
PeakSegDP results |
Documentation:
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