colorClusters

a clustering set as returned by <code><a rd-options="" href="/link/clusterTimeseries?package=segmenTier&version=0.1.2" data-mini-rdoc="segmenTier::clusterTimeseries">clusterTimeseries</a></code>

cset

a function that generates <code>n</code> colors

colf

arguments to color function <code>colf</code>

Takes a clustering set as returned by <code><a rd-options="" href="/link/clusterTimeseries?package=segmenTier&version=0.1.2" data-mini-rdoc="segmenTier::clusterTimeseries">clusterTimeseries</a></code> and
assigns colors to each cluster in each clustering along
the "hue" color wheel, as in <code>scale_colour_hue</code> in <code>ggplot2</code>.
If <code>cset</code> contains a sorting, this sorting will be used to assign
colors along the color wheel, otherwise a sorting will be calculated first,
using <code><a rd-options="" href="/link/sortClusters?package=segmenTier&version=0.1.2" data-mini-rdoc="segmenTier::sortClusters">sortClusters</a></code>.

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.

Rainer Machne

segmenTier

Similarity-Based Segmentation of Multidimensional Signals

colorClusters function

a clustering set as returned by <code><a rd-options='' href='clusterTimeseries'>clusterTimeseries</a></code>

Takes a clustering set as returned by <code><a rd-options='' href='clusterTimeseries'>clusterTimeseries</a></code> and
assigns colors to each cluster in each clustering along
the "hue" color wheel, as in <code>scale_colour_hue</code> in <code>ggplot2</code>.
If <code>cset</code> contains a sorting, this sorting will be used to assign
colors along the color wheel, otherwise a sorting will be calculated first,
using <code><a rd-options='' href='sortClusters'>sortClusters</a></code>.

colorClusters: Assign colors to clusters.

Description

Usage

Arguments

Value