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jointseg

This package implements functions to quickly segment multivariate signals into piecewise-constant profiles, as well as a framework to generate realistic copy-number profiles. A typical application is the joint segmentation of total DNA copy numbers and allelic ratios obtained from Single Nucleotide Polymorphism (SNP) microarrays in cancer studies.

Installation

You can install jointseg from github with:

# install.packages("devtools")
devtools::install_github("mpierrejean/jointseg")

Usage

The main high-level joint segmentation functions are:

  • jointSeg for arbitrary signals, see ?jointSeg.
  • PSSeg for bivariate copy-number signals, see ?PSSeg and vignette("PSSeg").

We also refer to vignette("dataGeneration") for a description of the generation of synthetic DNA copy-number profiles using data from the acnr package.

References

Pierre-Jean, M, Rigaill, G. J. and Neuvial, P. (2015). "Performance Evaluation of DNA Copy Number Segmentation Methods." Briefings in Bioinformatics, no. 4: 600–615.

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Platforms:MultipleLinux & OS XWindows
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Install

install.packages('jointseg')

Monthly Downloads

585

Version

1.0.3

License

LGPL (>= 2.1)

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Maintainer

Morgane Pierre-Jean

Last Published

May 14th, 2025

Functions in jointseg (1.0.3)

jointSeg

Joint segmentation of multivariate signals
mapPositionsBack

mapPositionsBack
leftMultiplyByXt

leftMultiplyByXt
leftMultiplyByInvXAtXA

leftMultiplyByInvXAtXA
getCopyNumberDataByResampling

Generate a copy number profile by resampling
estimateSd

Robust standard deviation estimator
doRBS

Run RBS segmentation
getTpFp

Calculate the number of true positives and false positives
getUnivStat

Get the binary test statistic for one dimension
getUnivJ

Get the contribution of one dimension to the RSE.
segmentByGFLars

Group fused Lars segmentation (low-level)
modelSelection

Model selection
randomProfile

Generate a random multi-dimensional profile with breakpoints and noise
plotSeg

Plot signal and breakpoints with segment-level signal estimates
retour_sn

Extract endpoint matrix from DP result
oneBkp

Get best candidate change point
pruneByDP

Exact segmentation of a multivariate signal using dynamic programming.
segmentByRBS

Recursive Binary Segmentation (low-level)
prof

profile time and memory usage of a given R expression
multiplyXtXBySparse

multiplyXtXBySparse
binMissingValues

binMissingValues
doGFLars

Group fused Lars segmentation
doPSCN

Run PSCN segmentation (defunct)
doPSCBS

Run Paired PSCBS segmentation
Fpsn

Pruned dynamic programming algorithm
defaultWeights

Compute default weights for the weighted group fused Lasso
PSSeg

Parent-Specific copy number segmentation
doDynamicProgramming

Run segmentation by dynamic programming
doCBS

Run CBS segmentation
anotherBkp

Get best candidate change point