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segmenTier  

Similarity-Based Segmentation of Multidimensional Signals
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]
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. Accessed 02 May. 2025.
Previous versions and publish date:
No previous versions
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Complete documentation for segmenTier
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