Package: segmenTier
Type: Package
Title: Similarity-Based Segmentation of Multidimensional Signals
Version: 0.1.3
Author: Rainer Machne, Douglas B. Murray, Peter F. Stadler
URL: https://github.com/raim/segmenTier
BugReports: https://github.com/raim/segmenTier/issues
Maintainer: Rainer Machne <raim@tbi.univie.ac.at>
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)
        <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.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.7)
Suggests: flowMerge, flowClust, flowCore, knitr, rmarkdown
LinkingTo: Rcpp
Encoding: UTF-8
RoxygenNote: 7.3.2
VignetteBuilder: knitr
Repository: https://raim.r-universe.dev
Date/Publication: 2025-07-17 09:59:52 UTC
RemoteUrl: https://github.com/raim/segmentier
RemoteRef: HEAD
RemoteSha: 91505fd75333466c9568b66112b037a7cdd09b73
RemoteSubdir: pkg
NeedsCompilation: yes
Packaged: 2026-07-15 05:37:22 UTC; root