Similarity-Based Segmentation of Multidimensional Signals
Overview
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) doi:10.1038/s41598-017-12401-8. 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) doi:10.1371/journal.pone.0037906), 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.
Install
Health
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Rainer Machne <raim@tbi.univie.ac.at>’
No Authors@R field in DESCRIPTION.
Please add one, modifying
Authors@R: c(person(given = "Rainer",
family = "Machne",
role = c("aut", "cre"),
email = "raim@tbi.univie.ac.at"),
person(given = c("Douglas", "B."),
family = "Murray",
role = "aut"),
person(given = c("Peter", "F."),
family = "Stadler",
role = "aut"))
as necessary.- NOTE11 OK, 2 NOTENow
- NOTE12 OK, 2 NOTE2026-04-22
- ERROR11 OK, 2 NOTE, 1 ERROR2026-04-18
- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- Help pages
- 23includes a package overview page
- Examples that run
- 100%4 run in a plain check
- Exported functions with examples
- 27%
- Documented parameters
- 100%
- Return-value docs
- 60%
- Help pages citing references
- 26%
Also includes 2 demo scripts (run with demo())
Downloads
Repository
- PRs merged (all time)
- 100%
- Median days to close, 50 most recently updated closed issues
- not measured
- Median days to close, 50 most recently updated closed PRs
- 0
Stars over time
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Checks run against github.com/raim/segmentier on 2026-10-21.
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Dependencies
Installing segmenTier adds 1 package (1 with compiled code, 1.8 MB of source tarballs). Heaviest: Rcpp 1.8 MB.
Code & Tests
Datasets
People & History
Maintainer since 0.1.2 (2019)
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- 0.1.2Latest2019-02-18 · current release
- RR 3.5.0 released · 2018-04-23
Package metadata
- First published
- 2019-02-18
- Total releases
- 1 / 7 yrs
- License
- GPL (>= 2) OSI
- Bundled data
- 175 KB / 1 file
- Download size
- 692 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("segmenTier")Cite the R Observatory
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