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segmenTier
View on CRAN: Click
here
Download and install segmenTier package within the R console
Install from CRAN:
install.packages("segmenTier")
Install from Github:
library("remotes")
install_github("cran/segmenTier")
Install by package version:
library("remotes")
install_version("segmenTier", "0.1.2")
Attach the package and use:
library("segmenTier")
Maintained by
Rainer Machne
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-02-18
Latest Update: 2019-02-18
Description:
A dynamic programming solution to segmentation based on
maximization of arbitrary similarity measures within segments.
The general idea, theory and this implementation are described in
Machne, Murray & Stadler (2017) .
In addition to the core algorithm, the package provides time-series
processing and clustering functions as described in the publication.
These are generally applicable where a `k-means` clustering yields
meaningful results, and have been specifically developed for
clustering of the Discrete Fourier Transform of periodic gene
expression data (`circadian' or `yeast metabolic oscillations').
This clustering approach is outlined in the supplemental material of
Machne & Murray (2012) ), and here
is used as a basis of segment similarity measures. Notably, the
time-series processing and clustering functions can also be used as
stand-alone tools, independent of segmentation, e.g., for
transcriptome data already mapped to genes.
How to cite:
Rainer Machne (2019). segmenTier: Similarity-Based Segmentation of Multidimensional Signals. R package version 0.1.2, https://cran.r-project.org/web/packages/segmenTier
Previous versions and publish date:
No previous versions
Other packages that cited segmenTier R package
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Other R packages that segmenTier depends,
imports, suggests or enhances
Functions, R codes and Examples using
the segmenTier R package
Some associated functions: ash . backtrace . calculateScore . clusterCor_c . clusterTimeseries . colorClusters . flowclusterTimeseries . logLik.kmeans . log_1 . myPearson . plot.clustering . plot.segments . plot.timeseries . plotSegmentation . plotdev . print.segments . processTimeseries . segmenTier . segmentCluster.batch . segmentClusters . setVarySettings . sortClusters . tsd .
Some associated R codes: RcppExports.R . cluster.R . plot.R . segment.R . Full segmenTier package functions and examples
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