PeakSegJointHeuristicStep2

List of data.frames with columns chromStart, chromEnd, count, or
single data.frame with additional column sample.id.

profiles

Size of bin pyramid. Bigger values result in slower computation.

bin.factor

Run the first and second steps of the PeakSegJoint fast heuristic
optimization algorithm. Step2 the SearchNearPeak subroutine
described in the JointZoom Algorithm of arXiv:1506.01286, and it
is guaranteed to return feasible segmentations (seg1 &lt; seg2 &gt;
seg3). NB: this function is only for testing the C code against
the R implementation (search tests/testthat/*.R files for
Step2). For real data see <code><a rd-options="" href="/link/PeakSegJointSeveral?package=PeakSegJoint&version=2022.4.6" data-mini-rdoc="PeakSegJoint::PeakSegJointSeveral">PeakSegJointSeveral</a></code>.

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.

Toby Hocking

PeakSegJoint

Joint Peak Detection in Several ChIP-Seq Samples

PeakSegJointHeuristicStep2 function

Run the first and second steps of the PeakSegJoint fast heuristic
optimization algorithm. Step2 the SearchNearPeak subroutine
described in the JointZoom Algorithm of arXiv:1506.01286, and it
is guaranteed to return feasible segmentations (seg1 &lt; seg2 &gt;
seg3). NB: this function is only for testing the C code against
the R implementation (search tests/testthat/*.R files for
Step2). For real data see <code><a rd-options='' href='PeakSegJointSeveral'>PeakSegJointSeveral</a></code>.

PeakSegJointHeuristicStep2: PeakSegJointHeuristicStep2

Description

Usage

Arguments

Value